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Computer Science Graduate Projects and Theses

Theses/dissertations from 2023 2023.

High-Performance Domain-Specific Library for Hydrologic Data Processing , Kalyan Bhetwal

Verifying Data Provenance During Workflow Execution for Scientific Reproducibility , Rizbanul Hasan

Remote Sensing to Advance Understanding of Snow-Vegetation Relationships and Quantify Snow Depth and Snow Water Equivalent , Ahmad Hojatimalekshah

Exploring the Capability of a Self-Supervised Conditional Image Generator for Image-to-Image Translation without Labeled Data: A Case Study in Mobile User Interface Design , Hailee Kiesecker

Fake News Detection Using Narrative Content and Discourse , Hongmin Kim

Anomaly Detection Using Graph Neural Network , Bishal Lakha

Sparse Format Conversion and Code Synthesis , Tobi Goodness Popoola

Portable Sparse Polyhedral Framework Code Generation Using Multi Level Intermediate Representation , Aaron St. George

Severity Measures for Assessing Error in Automatic Speech Recognition , Ryan Whetten

Theses/Dissertations from 2022 2022

Improved Computational Prediction of Function and Structural Representation of Self-Cleaving Ribozymes with Enhanced Parameter Selection and Library Design , James D. Beck

Meshfree Methods for PDEs on Surfaces , Andrew Michael Jones

Deep Learning of Microstructures , Amir Abbas Kazemzadeh Farizhandi

Long-Term Trends in Extreme Environmental Events with Changepoint Detection , Mintaek Lee

Structure Aware Smart Encoding and Decoding of Information in DNA , Shoshanna Llewellyn

Towards Making Transformer-Based Language Models Learn How Children Learn , Yousra Mahdy

Ontology-Based Formal Approach for Safety and Security Verification of Industrial Control Systems , Ramesh Neupane

Improving Children's Authentication Practices with Respect to Graphical Authentication Mechanism , Dhanush Kumar Ratakonda

Hate Speech Detection Using Textual and User Features , Rohan Raut

Automated Detection of Sockpuppet Accounts in Wikipedia , Mostofa Najmus Sakib

Characterization and Mitigation of False Information on the Web , Anu Shrestha

Sinusoidal Projection for 360° Image Compression and Triangular Discrete Cosine Transform Impact in the JPEG Pipeline , Iker Vazquez Lopez

Theses/Dissertations from 2021 2021

Training Wheels for Web Search: Multi-Perspective Learning to Rank to Support Children's Information Seeking in the Classroom , Garrett Allen

Fair and Efficient Consensus Protocols for Secure Blockchain Applications , Golam Dastoger Bashar

Why Don't You Act Your Age?: Recognizing the Stereotypical 8-12 Year Old Searcher by Their Search Behavior , Michael Green

Ensuring Consistency and Efficiency of the Incremental Unit Network in a Distributed Architecture , Mir Tahsin Imtiaz

Modeling Real and Fake News Sharing in Social Networks , Abishai Joy

Modeling and Analyzing Users' Privacy Disclosure Behavior to Generate Personalized Privacy Policies , A.K.M. Nuhil Mehdy

Into the Unknown: Exploration of Search Engines' Responses to Users with Depression and Anxiety , Ashlee Milton

Generating Test Inputs from String Constraints with an Automata-Based Solver , Marlin Roberts

A Case Study in Representing Scientific Applications ( GeoAc ) Using the Sparse Polyhedral Framework , Ravi Shankar

Actors for the Internet of Things , Arjun Shukla

Theses/Dissertations from 2020 2020

Towards Unifying Grounded and Distributional Semantics Using the Words-as-Classifiers Model of Lexical Semantics , Stacy Black

Improving Scientist Productivity, Architecture Portability, and Performance in ParFlow , Michael Burke

Polyhedral+Dataflow Graphs , Eddie C. Davis

Improving Spellchecking for Children: Correction and Design , Brody Downs

A Collection of Fast Algorithms for Scalar and Vector-Valued Data on Irregular Domains: Spherical Harmonic Analysis, Divergence-Free/Curl-Free Radial Basis Functions, and Implicit Surface Reconstruction , Kathryn Primrose Drake

Privacy-Preserving Protocol for Atomic Swap Between Blockchains , Kiran Gurung

Unsupervised Structural Graph Node Representation Learning , Mikel Joaristi

Detecting Undisclosed Paid Editing in Wikipedia , Nikesh Joshi

Do You Feel Me?: Learning Language from Humans with Robot Emotional Displays , David McNeill

Obtaining Real-World Benchmark Programs from Open-Source Repositories Through Abstract-Semantics Preserving Transformations , Maria Anne Rachel Paquin

Content Based Image Retrieval (CBIR) for Brand Logos , Enjal Parajuli

A Resilience Metric for Modern Power Distribution Systems , Tyler Bennett Phillips

Theses/Dissertations from 2019 2019

Edge-Assisted Workload-Aware Image Processing System , Anil Acharya

MINOS: Unsupervised Netflow-Based Detection of Infected and Attacked Hosts, and Attack Time in Large Networks , Mousume Bhowmick

Deviant: A Mutation Testing Tool for Solidity Smart Contracts , Patrick Chapman

Querying Over Encrypted Databases in a Cloud Environment , Jake Douglas

A Hybrid Model to Detect Fake News , Indhumathi Gurunathan

Suitability of Finite State Automata to Model String Constraints in Probablistic Symbolic Execution , Andrew Harris

UNICORN Framework: A User-Centric Approach Toward Formal Verification of Privacy Norms , Rezvan Joshaghani

Detection and Countermeasure of Saturation Attacks in Software-Defined Networks , Samer Yousef Khamaiseh

Secure Two-Party Protocol for Privacy-Preserving Classification via Differential Privacy , Manish Kumar

Application-Specific Memory Subsystem Benchmarking , Mahesh Lakshminarasimhan

Multilingual Information Retrieval: A Representation Building Perspective , Ion Madrazo

Improved Study of Side-Channel Attacks Using Recurrent Neural Networks , Muhammad Abu Naser Rony Chowdhury

Investigating the Effects of Social and Temporal Dynamics in Fitness Games on Children's Physical Activity , Ankita Samariya

BullyNet: Unmasking Cyberbullies on Social Networks , Aparna Sankaran

FALCON: Framework for Anomaly Detection In Industrial Control Systems , Subin Sapkota

Investigating Semantic Properties of Images Generated from Natural Language Using Neural Networks , Samuel Ward Schrader

Incremental Processing for Improving Conversational Grounding in a Chatbot , Aprajita Shukla

Estimating Error and Bias of Offline Recommender System Evaluation Results , Mucun Tian

Theses/Dissertations from 2018 2018

Leveraging Tiled Display for Big Data Visualization Using D3.js , Ujjwal Acharya

Fostering the Retrieval of Suitable Web Resources in Response to Children's Educational Search Tasks , Oghenemaro Deborah Anuyah

Privacy-Preserving Genomic Data Publishing via Differential Privacy , Tanya Khatri

Injecting Control Commands Through Sensory Channel: Attack and Defense , Farhad Rasapour

Strong Mutation-Based Test Generation of XACML Policies , Roshan Shrestha

Performance, Scalability, and Robustness in Distributed File Tree Copy , Christopher Robert Sutton

Using DNA For Data Storage: Encoding and Decoding Algorithm Development , Kelsey Suyehira

Detecting Saliency by Combining Speech and Object Detection in Indoor Environments , Kiran Thapa

Theses/Dissertations from 2017 2017

Identifying Restaurants Proposing Novel Kinds of Cuisines: Using Yelp Reviews , Haritha Akella

Editing Behavior Analysis and Prediction of Active/Inactive Users in Wikipedia , Harish Arelli

CloudSkulk: Design of a Nested Virtual Machine Based Rootkit-in-the-Middle Attack , Joseph Anthony Connelly

Predicting Friendship Strength in Facebook , Nitish Dhakal

Privacy-Preserving Trajectory Data Publishing via Differential Privacy , Ishita Dwivedi

Cultivating Community Interactions in Citizen Science: Connecting People to Each Other and the Environment , Bret Allen Finley

Uncovering New Links Through Interaction Duration , Laxmi Amulya Gundala

Variance: Secure Two-Party Protocol for Solving Yao's Millionaires' Problem in Bitcoin , Joshua Holmes

A Scalable Graph-Coarsening Based Index for Dynamic Graph Databases , Akshay Kansal

Integrity Coded Databases: Ensuring Correctness and Freshness of Outsourced Databases , Ujwal Karki

Editable View Optimized Tone Mapping For Viewing High Dynamic Range Panoramas On Head Mounted Display , Yuan Li

The Effects of Pair-Programming in a High School Introductory Computer Science Class , Ken Manship

Towards Automatic Repair of XACML Policies , Shuai Peng

Identification of Unknown Landscape Types Using CNN Transfer Learning , Ashish Sharma

Hand Gesture Recognition for Sign Language Transcription , Iker Vazquez Lopez

Learning to Code Music : Development of a Supplemental Unit for High School Computer Science , Kelsey Wright

Theses/Dissertations from 2016 2016

Identification of Small Endogenous Viral Elements within Host Genomes , Edward C. Davis Jr.

When the System Becomes Your Personal Docent: Curated Book Recommendations , Nevena Dragovic

Security Testing with Misuse Case Modeling , Samer Yousef Khamaiseh

Estimating Length Statistics of Aggregate Fried Potato Product via Electromagnetic Radiation Attenuation , Jesse Lovitt

Towards Multipurpose Readability Assessment , Ion Madrazo

Evaluation of Topic Models for Content-Based Popularity Prediction on Social Microblogs , Axel Magnuson

CEST: City Event Summarization using Twitter , Deepa Mallela

Developing an ABAC-Based Grant Proposal Workflow Management System , Milson Munakami

Phoenix and Hive as Alternatives to RDBMS , Diana Ornelas

Massively Parallel Algorithm for Solving the Eikonal Equation on Multiple Accelerator Platforms , Anup Shrestha

A Certificateless One-Way Group Key Agreement Protocol for Point-to-Point Email Encryption , Srisarguru Sridhar

Dynamic Machine Level Resource Allocation to Improve Tasking Performance Across Multiple Processes , Richard Walter Thatcher

Theses/Dissertations from 2015 2015

Developing an Application for Evolutionary Search for Computational Models of Cellular Development , Nicolas Scott Cornia

Accelerated Radar Signal Processing in Large Geophysical Datasets , Ravi Preesha Geetha

Integrity Coded Databases (ICDB) – Protecting Integrity for Outsourced Databases , Archana Nanjundarao

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Research Topics & Ideas: CompSci & IT

50+ Computer Science Research Topic Ideas To Fast-Track Your Project

Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you’ve landed on this post, chances are you’re looking for a computer science-related research topic , but aren’t sure where to start. Here, we’ll explore a variety of CompSci & IT-related research ideas and topic thought-starters, including algorithms, AI, networking, database systems, UX, information security and software engineering.

NB – This is just the start…

The topic ideation and evaluation process has multiple steps . In this post, we’ll kickstart the process by sharing some research topic ideas within the CompSci domain. This is the starting point, but to develop a well-defined research topic, you’ll need to identify a clear and convincing research gap , along with a well-justified plan of action to fill that gap.

If you’re new to the oftentimes perplexing world of research, or if this is your first time undertaking a formal academic research project, be sure to check out our free dissertation mini-course. In it, we cover the process of writing a dissertation or thesis from start to end. Be sure to also sign up for our free webinar that explores how to find a high-quality research topic. 

Overview: CompSci Research Topics

• Algorithms & data structures
• Artificial intelligence ( AI )
• Computer networking
• Database systems
• Human-computer interaction
• Information security (IS)
• Software engineering
• Examples of CompSci dissertation & theses

Topics/Ideas: Algorithms & Data Structures

• An analysis of neural network algorithms’ accuracy for processing consumer purchase patterns
• A systematic review of the impact of graph algorithms on data analysis and discovery in social media network analysis
• An evaluation of machine learning algorithms used for recommender systems in streaming services
• A review of approximation algorithm approaches for solving NP-hard problems
• An analysis of parallel algorithms for high-performance computing of genomic data
• The influence of data structures on optimal algorithm design and performance in Fintech
• A Survey of algorithms applied in internet of things (IoT) systems in supply-chain management
• A comparison of streaming algorithm performance for the detection of elephant flows
• A systematic review and evaluation of machine learning algorithms used in facial pattern recognition
• Exploring the performance of a decision tree-based approach for optimizing stock purchase decisions
• Assessing the importance of complete and representative training datasets in Agricultural machine learning based decision making.
• A Comparison of Deep learning algorithms performance for structured and unstructured datasets with “rare cases”
• A systematic review of noise reduction best practices for machine learning algorithms in geoinformatics.
• Exploring the feasibility of applying information theory to feature extraction in retail datasets.
• Assessing the use case of neural network algorithms for image analysis in biodiversity assessment

Topics & Ideas: Artificial Intelligence (AI)

• Applying deep learning algorithms for speech recognition in speech-impaired children
• A review of the impact of artificial intelligence on decision-making processes in stock valuation
• An evaluation of reinforcement learning algorithms used in the production of video games
• An exploration of key developments in natural language processing and how they impacted the evolution of Chabots.
• An analysis of the ethical and social implications of artificial intelligence-based automated marking
• The influence of large-scale GIS datasets on artificial intelligence and machine learning developments
• An examination of the use of artificial intelligence in orthopaedic surgery
• The impact of explainable artificial intelligence (XAI) on transparency and trust in supply chain management
• An evaluation of the role of artificial intelligence in financial forecasting and risk management in cryptocurrency
• A meta-analysis of deep learning algorithm performance in predicting and cyber attacks in schools

Topics & Ideas: Networking

• An analysis of the impact of 5G technology on internet penetration in rural Tanzania
• Assessing the role of software-defined networking (SDN) in modern cloud-based computing
• A critical analysis of network security and privacy concerns associated with Industry 4.0 investment in healthcare.
• Exploring the influence of cloud computing on security risks in fintech.
• An examination of the use of network function virtualization (NFV) in telecom networks in Southern America
• Assessing the impact of edge computing on network architecture and design in IoT-based manufacturing
• An evaluation of the challenges and opportunities in 6G wireless network adoption
• The role of network congestion control algorithms in improving network performance on streaming platforms
• An analysis of network coding-based approaches for data security
• Assessing the impact of network topology on network performance and reliability in IoT-based workspaces

Topics & Ideas: Database Systems

• An analysis of big data management systems and technologies used in B2B marketing
• The impact of NoSQL databases on data management and analysis in smart cities
• An evaluation of the security and privacy concerns of cloud-based databases in financial organisations
• Exploring the role of data warehousing and business intelligence in global consultancies
• An analysis of the use of graph databases for data modelling and analysis in recommendation systems
• The influence of the Internet of Things (IoT) on database design and management in the retail grocery industry
• An examination of the challenges and opportunities of distributed databases in supply chain management
• Assessing the impact of data compression algorithms on database performance and scalability in cloud computing
• An evaluation of the use of in-memory databases for real-time data processing in patient monitoring
• Comparing the effects of database tuning and optimization approaches in improving database performance and efficiency in omnichannel retailing

Topics & Ideas: Human-Computer Interaction

• An analysis of the impact of mobile technology on human-computer interaction prevalence in adolescent men
• An exploration of how artificial intelligence is changing human-computer interaction patterns in children
• An evaluation of the usability and accessibility of web-based systems for CRM in the fast fashion retail sector
• Assessing the influence of virtual and augmented reality on consumer purchasing patterns
• An examination of the use of gesture-based interfaces in architecture
• Exploring the impact of ease of use in wearable technology on geriatric user
• Evaluating the ramifications of gamification in the Metaverse
• A systematic review of user experience (UX) design advances associated with Augmented Reality
• A comparison of natural language processing algorithms automation of customer response Comparing end-user perceptions of natural language processing algorithms for automated customer response
• Analysing the impact of voice-based interfaces on purchase practices in the fast food industry

Topics & Ideas: Information Security

• A bibliometric review of current trends in cryptography for secure communication
• An analysis of secure multi-party computation protocols and their applications in cloud-based computing
• An investigation of the security of blockchain technology in patient health record tracking
• A comparative study of symmetric and asymmetric encryption algorithms for instant text messaging
• A systematic review of secure data storage solutions used for cloud computing in the fintech industry
• An analysis of intrusion detection and prevention systems used in the healthcare sector
• Assessing security best practices for IoT devices in political offices
• An investigation into the role social media played in shifting regulations related to privacy and the protection of personal data
• A comparative study of digital signature schemes adoption in property transfers
• An assessment of the security of secure wireless communication systems used in tertiary institutions

Topics & Ideas: Software Engineering

• A study of agile software development methodologies and their impact on project success in pharmacology
• Investigating the impacts of software refactoring techniques and tools in blockchain-based developments
• A study of the impact of DevOps practices on software development and delivery in the healthcare sector
• An analysis of software architecture patterns and their impact on the maintainability and scalability of cloud-based offerings
• A study of the impact of artificial intelligence and machine learning on software engineering practices in the education sector
• An investigation of software testing techniques and methodologies for subscription-based offerings
• A review of software security practices and techniques for protecting against phishing attacks from social media
• An analysis of the impact of cloud computing on the rate of software development and deployment in the manufacturing sector
• Exploring the impact of software development outsourcing on project success in multinational contexts
• An investigation into the effect of poor software documentation on app success in the retail sector

CompSci & IT Dissertations/Theses

While the ideas we’ve presented above are a decent starting point for finding a CompSci-related research topic, they are fairly generic and non-specific. So, it helps to look at actual dissertations and theses to see how this all comes together.

Below, we’ve included a selection of research projects from various CompSci-related degree programs to help refine your thinking. These are actual dissertations and theses, written as part of Master’s and PhD-level programs, so they can provide some useful insight as to what a research topic looks like in practice.

• An array-based optimization framework for query processing and data analytics (Chen, 2021)
• Dynamic Object Partitioning and replication for cooperative cache (Asad, 2021)
• Embedding constructural documentation in unit tests (Nassif, 2019)
• PLASA | Programming Language for Synchronous Agents (Kilaru, 2019)
• Healthcare Data Authentication using Deep Neural Network (Sekar, 2020)
• Virtual Reality System for Planetary Surface Visualization and Analysis (Quach, 2019)
• Artificial neural networks to predict share prices on the Johannesburg stock exchange (Pyon, 2021)
• Predicting household poverty with machine learning methods: the case of Malawi (Chinyama, 2022)
• Investigating user experience and bias mitigation of the multi-modal retrieval of historical data (Singh, 2021)
• Detection of HTTPS malware traffic without decryption (Nyathi, 2022)
• Redefining privacy: case study of smart health applications (Al-Zyoud, 2019)
• A state-based approach to context modeling and computing (Yue, 2019)
• A Novel Cooperative Intrusion Detection System for Mobile Ad Hoc Networks (Solomon, 2019)
• HRSB-Tree for Spatio-Temporal Aggregates over Moving Regions (Paduri, 2019)

Looking at these titles, you can probably pick up that the research topics here are quite specific and narrowly-focused , compared to the generic ones presented earlier. This is an important thing to keep in mind as you develop your own research topic. That is to say, to create a top-notch research topic, you must be precise and target a specific context with specific variables of interest . In other words, you need to identify a clear, well-justified research gap.

Fast-Track Your Research Topic

If you’re still feeling a bit unsure about how to find a research topic for your Computer Science dissertation or research project, check out our Topic Kickstarter service.

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Investigating the impacts of software refactoring techniques and tools in blockchain-based developments.

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100 Great Computer Science Research Topics Ideas for 2023

Being a computer student in 2023 is not easy. Besides studying a constantly evolving subject, you have to come up with great computer science research topics at some point in your academic life. If you’re reading this article, you’re among many other students that have also come to this realization.

Interesting Computer Science Topics

Awesome research topics in computer science, hot topics in computer science, topics to publish a journal on computer science.

• Controversial Topics in Computer Science

Fun AP Computer Science Topics

Exciting computer science ph.d. topics, remarkable computer science research topics for undergraduates, incredible final year computer science project topics, advanced computer science topics, unique seminars topics for computer science, exceptional computer science masters thesis topics, outstanding computer science presentation topics.

• Key Computer Science Essay Topics

Main Project Topics for Computer Science

• We Can Help You with Computer Science Topics

Whether you’re earnestly searching for a topic or stumbled onto this article by accident, there is no doubt that every student needs excellent computer science-related topics for their paper. A good topic will not only give your essay or research a good direction but will also make it easy to come up with supporting points. Your topic should show all your strengths as well.

Fortunately, this article is for every student that finds it hard to generate a suitable computer science topic. The following 100+ topics will help give you some inspiration when creating your topics. Let’s get into it.

One of the best ways of making your research paper interesting is by coming up with relevant topics in computer science . Here are some topics that will make your paper immersive:

• Evolution of virtual reality
• What is green cloud computing
• Ways of creating a Hopefield neural network in C++
• Developments in graphic systems in computers
• The five principal fields in robotics
• Developments and applications of nanotechnology
• Differences between computer science and applied computing

Your next research topic in computer science shouldn’t be tough to find once you’ve read this section. If you’re looking for simple final year project topics in computer science, you can find some below.

• Applications of the blockchain technology in the banking industry
• Computational thinking and how it influences science
• Ways of terminating phishing
• Uses of artificial intelligence in cyber security
• Define the concepts of a smart city
• Applications of the Internet of Things
• Discuss the applications of the face detection application

Whenever a topic is described as “hot,” it means that it is a trendy topic in computer science. If computer science project topics for your final years are what you’re looking for, have a look at some below:

• Applications of the Metaverse in the world today
• Discuss the challenges of machine learning
• Advantages of artificial intelligence
• Applications of nanotechnology in the paints industry
• What is quantum computing?
• Discuss the languages of parallel computing
• What are the applications of computer-assisted studies?

Perhaps you’d like to write a paper that will get published in a journal. If you’re searching for the best project topics for computer science students that will stand out in a journal, check below:

• Developments in human-computer interaction
• Applications of computer science in medicine
• Developments in artificial intelligence in image processing
• Discuss cryptography and its applications
• Discuss methods of ransomware prevention
• Applications of Big Data in the banking industry
• Challenges of cloud storage services in 2023

 Controversial Topics in Computer Science

Some of the best computer science final year project topics are those that elicit debates or require you to take a stand. You can find such topics listed below for your inspiration:

• Can robots be too intelligent?
• Should the dark web be shut down?
• Should your data be sold to corporations?
• Will robots completely replace the human workforce one day?
• How safe is the Metaverse for children?
• Will artificial intelligence replace actors in Hollywood?
• Are social media platforms safe anymore?

Are you a computer science student looking for AP topics? You’re in luck because the following final year project topics for computer science are suitable for you.

• Standard browser core with CSS support
• Applications of the Gaussian method in C++ development in integrating functions
• Vital conditions of reducing risk through the Newton method
• How to reinforce machine learning algorithms.
• How do artificial neural networks function?
• Discuss the advancements in computer languages in machine learning
• Use of artificial intelligence in automated cars

When studying to get your doctorate in computer science, you need clear and relevant topics that generate the reader’s interest. Here are some Ph.D. topics in computer science you might consider:

• Developments in information technology
• Is machine learning detrimental to the human workforce?
• How to write an algorithm for deep learning
• What is the future of 5G in wireless networks
• Statistical data in Maths modules in Python
• Data retention automation from a website using API
• Application of modern programming languages

Looking for computer science topics for research is not easy for an undergraduate. Fortunately, these computer science project topics should make your research paper easy:

• Ways of using artificial intelligence in real estate
• Discuss reinforcement learning and its applications
• Uses of Big Data in science and medicine
• How to sort algorithms using Haskell
• How to create 3D configurations for a website
• Using inverse interpolation to solve non-linear equations
• Explain the similarities between the Internet of Things and artificial intelligence

Your dissertation paper is one of the most crucial papers you’ll ever do in your final year. That’s why selecting the best ethics in computer science topics is a crucial part of your paper. Here are some project topics for the computer science final year.

• How to incorporate numerical methods in programming
• Applications of blockchain technology in cloud storage
• How to come up with an automated attendance system
• Using dynamic libraries for site development
• How to create cubic splines
• Applications of artificial intelligence in the stock market
• Uses of quantum computing in financial modeling

Your instructor may want you to challenge yourself with an advanced science project. Thus, you may require computer science topics to learn and research. Here are some that may inspire you:

• Discuss the best cryptographic protocols
• Advancement of artificial intelligence used in smartphones
• Briefly discuss the types of security software available
• Application of liquid robots in 2023
• How to use quantum computers to solve decoherence problem
• macOS vs. Windows; discuss their similarities and differences
• Explain the steps taken in a cyber security audit

When searching for computer science topics for a seminar, make sure they are based on current research or events. Below are some of the latest research topics in computer science:

• How to reduce cyber-attacks in 2023
• Steps followed in creating a network
• Discuss the uses of data science
• Discuss ways in which social robots improve human interactions
• Differentiate between supervised and unsupervised machine learning
• Applications of robotics in space exploration
• The contrast between cyber-physical and sensor network systems

Are you looking for computer science thesis topics for your upcoming projects? The topics below are meant to help you write your best paper yet:

• Applications of computer science in sports
• Uses of computer technology in the electoral process
• Using Fibonacci to solve the functions maximum and their implementations
• Discuss the advantages of using open-source software
• Expound on the advancement of computer graphics
• Briefly discuss the uses of mesh generation in computational domains
• How much data is generated from the internet of things?

A computer science presentation requires a topic relevant to current events. Whether your paper is an assignment or a dissertation, you can find your final year computer science project topics below:

• Uses of adaptive learning in the financial industry
• Applications of transitive closure on graph
• Using RAD technology in developing software
• Discuss how to create maximum flow in the network
• How to design and implement functional mapping
• Using artificial intelligence in courier tracking and deliveries
• How to make an e-authentication system

 Key Computer Science Essay Topics

You may be pressed for time and require computer science master thesis topics that are easy. Below are some topics that fit this description:

• What are the uses of cloud computing in 2023
• Discuss the server-side web technologies
• Compare and contrast android and iOS
• How to come up with a face detection algorithm
• What is the future of NFTs
• How to create an artificial intelligence shopping system
• How to make a software piracy prevention algorithm

One major mistake students make when writing their papers is selecting topics unrelated to the study at hand. This, however, will not be an issue if you get topics related to computer science, such as the ones below:

• Using blockchain to create a supply chain management system
• How to protect a web app from malicious attacks
• Uses of distributed information processing systems
• Advancement of crowd communication software since COVID-19
• Uses of artificial intelligence in online casinos
• Discuss the pillars of math computations
• Discuss the ethical concerns arising from data mining

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We understand what students go through when searching the internet for computer science research paper topics, and we know that many students don’t know how to write a research paper to perfection. However, you shouldn’t have to go through all this when we’re here to help.

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Home > College of Natural Sciences > COMPUTERSCI-ENGINEERING > COMPUTERSCI-ENGINEERING-ETD

Computer Science and Engineering Theses, Projects, and Dissertations

Theses/projects/dissertations from 2023 2023.

CLASSIFICATION OF LARGE SCALE FISH DATASET BY DEEP NEURAL NETWORKS , Priyanka Adapa

GEOSPATIAL WILDFIRE RISK PREDICTION USING DEEP LEARNING , Abner Alberto Benavides

HUMAN SUSPICIOUS ACTIVITY DETECTION , Nilamben Bhuva

MAX FIT EVENT MANAGEMENT WITH SALESFORCE , AKSHAY DAGWAR

MELANOMA DETECTION BASED ON DEEP LEARNING NETWORKS , Sanjay Devaraneni

Heart Disease Prediction Using Binary Classification , Virendra Sunil Devare

CLASSIFICATION OF THORAX DISEASES FROM CHEST X-RAY IMAGES , Sharad Jayusukhbhai Dobariya

WEB BASED MANAGEMENT SYSTEM FOR HOUSING SOCIETY , Likhitha Reddy Eddala

Sales and Stock Management System , Rashmika Gaddam Ms

CONTACTLESS FOOD ORDERING SYSTEM , Rishivar Kumar Goli

RESTAURANT MANAGEMENT WEBSITE , Akhil Sai Gollapudi

DISEASE OF LUNG INFECTION DETECTION USING CNN MODEL -BAYESIAN OPTIMIZATION , poojitha gutha

DATA POISONING ATTACKS ON PHASOR MEASUREMENT UNIT DATA , Rutuja Sanjeev Haridas

CRIME MAPPING ANALYSIS USING WEB APPLICATION. , Lavanya Krishnappa

A LONG-TERM FUNDS PREDICTOR BASED ON DEEP LEARNING , SHUIYI KUANG

LIVER SEGMENTATION AND LESION DETECTION IN MEDICAL IMAGES USING A DEEP LEARNING-BASED U-NET MODEL , Kaushik Mahida

PHASOR MEASUREMENT UNIT DATA VISUALIZATION , Nikhila Mandava

TWITTER POLICING , Hemanth Kumar Medisetty

TRANSACTION MANAGEMENT SYSYEM FOR A PUBLISHER , HASSAIN SHAREEF MOHAMMED JR

LOBANGU: AN OPTICAL CHARACTER RECOGNITION RECEIPT MANAGEMENT APP FOR HEALTH CENTER PHARMACIES IN THE D.R.CONGO AND SURROUNDING EASTERN AFRICAN COUNTRIES , Bénis Munganga

PREDICTIVE MODEL FOR CFPB CONSUMER COMPLAINTS , Vyshnavi Nalluri

REVIEW CLASSIFICATION USING NATURAL LANGUAGE PROCESSING AND DEEP LEARNING , Brian Nazareth

Brain Tumor Detection Using MRI Images , Mayur Patel

QUIZ WEB APPLICATION , Dipti Rathod

HYPOTHYROID DISEASE ANALYSIS BY USING MACHINE LEARNING , SANJANA SEELAM

Pillow Based Sleep Tracking Device Using Raspberry Pi , Venkatachalam Seviappan

FINSERV ANDROID APPLICATION , Harsh Piyushkumar Shah

AUTOMATED MEDICAL NOTES LABELLING AND CLASSIFICATION USING MACHINE LEARNING , Akhil Prabhakar Thota

GENETIC PROGRAMMING TO OPTIMIZE PERFORMANCE OF MACHINE LEARNING ALGORITHMS ON UNBALANCED DATA SET , Asitha Thumpati

GOVERNMENT AID PORTAL , Darshan Togadiya

GENERAL POPULATION PROJECTION MODEL WITH CENSUS POPULATION DATA , Takenori Tsuruga

LUNG LESION SEGMENTATION USING DEEP LEARNING APPROACHES , Sree Snigdha Tummala

DETECTION OF PHISHING WEBSITES USING MACHINE LEARNING , Saranya Valleri

Machine Learning for Kalman Filter Tuning Prediction in GPS/INS Trajectory Estimation , Peter Wright

Theses/Projects/Dissertations from 2022 2022

LEARN PROGRAMMING IN VIRTUAL REALITY? A PROJECT FOR COMPUTER SCIENCE STUDENTS , Benjamin Alexander

LUNG CANCER TYPE CLASSIFICATION , Mohit Ramajibhai Ankoliya

HIGH-RISK PREDICTION FOR COVID-19 PATIENTS USING MACHINE LEARNING , Raja Kajuluri

IMPROVING INDIA’S TRAFFIC MANAGEMENT USING INTELLIGENT TRANSPORTATION SYSTEMS , Umesh Makhloga

DETECTION OF EPILEPSY USING MACHINE LEARNING , Balamurugan Murugesan

SOCIAL MOBILE APPLICATION: UDROP , Mahmoud Oraiqat

Improved Sensor-Based Human Activity Recognition Via Hybrid Convolutional and Recurrent Neural Networks , Sonia Perez-Gamboa

College of Education FileMaker Extraction and End-User Database Development , Andrew Tran

DEEP LEARNING EDGE DETECTION IN IMAGE INPAINTING , Zheng Zheng

Theses/Projects/Dissertations from 2021 2021

A General Conversational Chatbot , Vipin Nambiar

Verification System , Paras Nigam

DESKTOP APPLICATION FOR THE PUZZLE BOARD GAME “RUSH HOUR” , Huanqing Nong

Ahmedabad City App , Rushabh Picha

COMPUTER SURVEILLANCE SYSTEM USING WI-FI FOR ANDROID , Shashank Reddy Saireddy

ANDROID PARKING SYSTEM , Vishesh Reddy Sripati

Sentiment Analysis: Stock Index Prediction with Multi-task Learning and Word Polarity Over Time , Yue Zhou

Theses/Projects/Dissertations from 2020 2020

BUBBLE-IN DIGITAL TESTING SYSTEM , Chaz Hampton

FEEDBACK REVIEW SYSTEM USING SENTIMENT ANALYSIS , Vineeth Kukkamalla

WEB APPLICATION FOR MOVIE PERFORMANCE PREDICTION , Devalkumar Patel

Theses/Projects/Dissertations from 2019 2019

REVIEWS TO RATING CONVERSION AND ANALYSIS USING MACHINE LEARNING TECHNIQUES , Charitha Chanamolu

EASY EXAM , SARTHAK DABHI

EXTRACT TRANSFORM AND LOADING TOOL FOR EMAIL , Amit Rajiv Lawanghare

VEHICLE INFORMATION SYSTEM USING BLOCKCHAIN , Amey Zulkanthiwar

Theses/Projects/Dissertations from 2018 2018

USING AUTOENCODER TO REDUCE THE LENGTH OF THE AUTISM DIAGNOSTIC OBSERVATION SCHEDULE (ADOS) , Sara Hussain Daghustani

California State University, San Bernardino Chatbot , Krutarth Desai

ORGANIZE EVENTS MOBILE APPLICATION , Thakshak Mani Chandra Reddy Gudimetla

SOCIAL NETWORK FOR SOFTWARE DEVELOPERS , Sanket Prabhakar Jadhav

VIRTUALIZED CLOUD PLATFORM MANAGEMENT USING A COMBINED NEURAL NETWORK AND WAVELET TRANSFORM STRATEGY , Chunyu Liu

INTER PROCESS COMMUNICATION BETWEEN TWO SERVERS USING MPICH , Nagabhavana Narla

SENSOR-BASED HUMAN ACTIVITY RECOGNITION USING BIDIRECTIONAL LSTM FOR CLOSELY RELATED ACTIVITIES , Arumugam Thendramil Pavai

NEURAL NETWORK ON VIRTUALIZATION SYSTEM, AS A WAY TO MANAGE FAILURE EVENTS OCCURRENCE ON CLOUD COMPUTING , Khoi Minh Pham

EPICCONFIGURATOR COMPUTER CONFIGURATOR AND CMS PLATFORM , IVO A. TANTAMANGO

STUDY ON THE PATTERN RECOGNITION ENHANCEMENT FOR MATRIX FACTORIZATIONS WITH AUTOMATIC RELEVANCE DETERMINATION , hau tao

Theses/Projects/Dissertations from 2017 2017

CHILDREN’S SOCIAL NETWORK: KIDS CLUB , Eiman Alrashoud

MULTI-WAY COMMUNICATION SYSTEM , S. Chinnam

WEB APPLICATION FOR GRADUATE COURSE RECOMMENDATION SYSTEM , Sayali Dhumal

MOBILE APPLICATION FOR ATTENDANCE SYSTEM COYOTE-ATTENDANCE , Sindhu Hari

WEB APPLICATION FOR GRADUATE COURSE ADVISING SYSTEM , Sanjay Karrolla

Custom T-Shirt Designs , Ranjan Khadka

STUDENT CLASS WAITING LIST ENROLLMENT , AISHWARYA LACHAGARI

ANDROID MOBILE APPLICATION FOR HOSPITAL EXECUTIVES , Vihitha Nalagatla

PIPPIN MACHINE , Kiran Reddy Pamulaparthy

SOUND MODE APPLICATION , Sindhuja Pogaku

I2MAPREDUCE: DATA MINING FOR BIG DATA , Vishnu Vardhan Reddy Sherikar

COMPARING AND IMPROVING FACIAL RECOGNITION METHOD , Brandon Luis Sierra

NATURAL LANGUAGE PROCESSING BASED GENERATOR OF TESTING INSTRUMENTS , Qianqian Wang

AUTOMATIC GENERATION OF WEB APPLICATIONS AND MANAGEMENT SYSTEM , Yu Zhou

Theses/Projects/Dissertations from 2016 2016

CLOTH - MODELING, DEFORMATION, AND SIMULATION , Thanh Ho

CoyoteLab - Linux Containers for Educational Use , Michael D. Korcha

PACKET FILTER APPROACH TO DETECT DENIAL OF SERVICE ATTACKS , Essa Yahya M Muharish

DATA MINING: TRACKING SUSPICIOUS LOGGING ACTIVITY USING HADOOP , Bir Apaar Singh Sodhi

Theses/Projects/Dissertations from 2015 2015

APPLY DATA CLUSTERING TO GENE EXPRESSION DATA , Abdullah Jameel Abualhamayl Mr.

Density Based Data Clustering , Rayan Albarakati

Developing Java Programs on Android Mobile Phones Using Speech Recognition , Santhrushna Gande

THE DESIGN AND IMPLEMENTATION OF AN ADAPTIVE CHESS GAME , Mehdi Peiravi

CALIFORNIA STATE UNIVERSITY SAN BERNARDINO WiN GPS , Francisco A. Ron

ESTIMATION ON GIBBS ENTROPY FOR AN ENSEMBLE , Lekhya Sai Sake

A WEB-BASED TEMPERATURE MONITORING SYSTEM FOR THE COLLEGE OF ARTS AND LETTERS , Rigoberto Solorio

ANTICS: A CROSS-PLATFORM MOBILE GAME , Gerren D. Willis

Theses/Projects/Dissertations from 2014 2014

Introducing Non-Determinism to the Parallel C Compiler , Rowen Concepcion

THE I: A CLIENT-BASED POINT-AND-CLICK PUZZLE GAME , Aldo Lewis

Interactive Student Planner Application , NII TETTEH TACKIE YARBOI

ANDROID MOBILE APPLICATION FOR CREST COMMUNITY CHURCH IN RIVERSIDE , Ran Wei

Proton Computed Tomography: Matrix Data Generation Through General Purpose Graphics Processing Unit Reconstruction , micah witt

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How to Contact Faculty for IW/Thesis Advising

Send the professor an e-mail. When you write a professor, be clear that you want a meeting regarding a senior thesis or one-on-one IW project, and briefly describe the topic or idea that you want to work on. Check the faculty listing for email addresses.

Parastoo Abtahi, Room 419

Available for single-semester IW and senior thesis advising, 2023-2024

• Research Areas: Human-Computer Interaction (HCI), Augmented Reality (AR), and Spatial Computing
• Input techniques for on-the-go interaction (e.g., eye-gaze, microgestures, voice) with a focus on uncertainty, disambiguation, and privacy.
• Minimal and timely multisensory output (e.g., spatial audio, haptics) that enables users to attend to their physical environment and the people around them, instead of a 2D screen.
• Interaction with intelligent systems (e.g., IoT, robots) situated in physical spaces with a focus on updating users’ mental model despite the complexity and dynamicity of these systems.

Ryan Adams, Room 411

Research areas:

• Machine learning driven design
• Generative models for structured discrete objects
• Approximate inference in probabilistic models
• Accelerating solutions to partial differential equations
• Innovative uses of automatic differentiation
• Modeling and optimizing 3d printing and CNC machining

Andrew Appel, Room 209

• Research Areas: Formal methods, programming languages, compilers, computer security.
• Software verification (for which taking COS 326 / COS 510 is helpful preparation)
• Game theory of poker or other games (for which COS 217 / 226 are helpful)
• Computer game-playing programs (for which COS 217 / 226)
•  Risk-limiting audits of elections (for which ORF 245 or other knowledge of probability is useful)

Sanjeev Arora, Room 407

• Theoretical machine learning, deep learning and its analysis, natural language processing. My advisees would typically have taken a course in algorithms (COS423 or COS 521 or equivalent) and a course in machine learning.
• Show that finding approximate solutions to NP-complete problems is also NP-complete (i.e., come up with NP-completeness reductions a la COS 487). 
• Experimental Algorithms: Implementing and Evaluating Algorithms using existing software packages. 
• Studying/designing provable algorithms for machine learning and implementions using packages like scipy and MATLAB, including applications in Natural language processing and deep learning.
• Any topic in theoretical computer science.

David August, Room 221

• Research Areas: Computer Architecture, Compilers, Parallelism
• Containment-based approaches to security:  We have designed and tested a simple hardware+software containment mechanism that stops incorrect communication resulting from faults, bugs, or exploits from leaving the system.   Let's explore ways to use containment to solve real problems.  Expect to work with corporate security and technology decision-makers.
• Parallelism: Studies show much more parallelism than is currently realized in compilers and architectures.  Let's find ways to realize this parallelism.
• Any other interesting topic in computer architecture or compilers. 

Mark Braverman, 194 Nassau St., Room 231

Available for Spring 2024 single-semester IW, only

• Research Areas: computational complexity, algorithms, applied probability, computability over the real numbers, game theory and mechanism design, information theory.
• Topics in computational and communication complexity.
• Applications of information theory in complexity theory.
• Algorithms for problems under real-life assumptions.
• Game theory, network effects
• Mechanism design (could be on a problem proposed by the student)

Sebastian Caldas, 221 Nassau Street, Room 105

• Research Areas: collaborative learning, machine learning for healthcare. Typically, I will work with students that have taken COS324.
• Methods for collaborative and continual learning.
• Machine learning for healthcare applications.

Bernard Chazelle, 194 Nassau St., Room 301

• Research Areas: Natural Algorithms, Computational Geometry, Sublinear Algorithms. 
• Natural algorithms (flocking, swarming, social networks, etc).
• Sublinear algorithms
• Self-improving algorithms
• Markov data structures

Danqi Chen, Room 412

Not available for IW or thesis advising, 2023-2024

• My advisees would be expected to have taken a course in machine learning and ideally have taken COS484 or an NLP graduate seminar.
• Representation learning for text and knowledge bases
• Pre-training and transfer learning
• Question answering and reading comprehension
• Information extraction
• Text summarization
• Any other interesting topics related to natural language understanding/generation

Marcel Dall'Agnol, Corwin 034

Available for single-semester and senior thesis advising, 2023-2024

• Research Areas: Theoretical computer science. (Specifically, quantum computation, sublinear algorithms, complexity theory, interactive proofs and cryptography)

Jia Deng, Room 423

Available for Fall 2023 single-semester IW, only

•  Research Areas: Computer Vision, Machine Learning.
• Object recognition and action recognition
• Deep Learning, autoML, meta-learning
• Geometric reasoning, logical reasoning

Adji Bousso Dieng, Room 406

• Research areas: Vertaix is a research lab at Princeton University led by Professor Adji Bousso Dieng. We work at the intersection of artificial intelligence (AI) and the natural sciences. The models and algorithms we develop are motivated by problems in those domains and contribute to advancing methodological research in AI. We leverage tools in statistical machine learning and deep learning in developing methods for learning with the data, of various modalities, arising from the natural sciences.

Robert Dondero, Corwin Hall, Room 038

• Research Areas:  Software engineering; software engineering education.
• Develop or evaluate tools to facilitate student learning in undergraduate computer science courses at Princeton, and beyond.
• In particular, can code critiquing tools help students learn about software quality?

Zeev Dvir, 194 Nassau St., Room 250

Not available for IW or thesis advising, 2023-2024.

• Research Areas: computational complexity, pseudo-randomness, coding theory and discrete mathematics.
• Independent Research: I have various research problems related to Pseudorandomness, Coding theory, Complexity and Discrete mathematics - all of which require strong mathematical background. A project could also be based on writing a survey paper describing results from a few theory papers revolving around some particular subject.

Benjamin Eysenbach, Room 416

• Research areas: reinforcement learning, machine learning. My advisees would typically have taken COS324.
• Using RL algorithms to applications in science and engineering.
• Emergent behavior of RL algorithms on high-fidelity robotic simulators.
• Studying how architectures and representations can facilitate generalization.

Christiane Fellbaum, 1-S-14 Green

No longer available for single-term IW and senior thesis advising, 2023-2024

• Research Areas: theoretical and computational linguistics, word sense disambiguation, lexical resource construction, English and multilingual WordNet(s), ontology
• Anything having to do with natural language--come and see me with/for ideas suitable to your background and interests. Some topics students have worked on in the past:
• Developing parsers, part-of-speech taggers, morphological analyzers for underrepresented languages (you don't have to know the language to develop such tools!)
• Quantitative approaches to theoretical linguistics questions
• Extensions and interfaces for WordNet (English and WN in other languages),
• Applications of WordNet(s), including:
• Foreign language tutoring systems,
• Spelling correction software,
• Word-finding/suggestion software for ordinary users and people with memory problems,
• Machine Translation 
• Sentiment and Opinion detection
• Automatic reasoning and inferencing
• Collaboration with professors in the social sciences and humanities ("Digital Humanities")

Adam Finkelstein, Room 424 

• Research Areas: computer graphics, audio.

Robert S. Fish, Corwin Hall, Room 037

No longer available for single-semester IW and senior thesis advising, 2023-2024

• Networking and telecommunications
• Learning, perception, and intelligence, artificial and otherwise;
• Human-computer interaction and computer-supported cooperative work
• Online education, especially in Computer Science Education
• Topics in research and development innovation methodologies including standards, open-source, and entrepreneurship
• Distributed autonomous organizations and related blockchain technologies

Michael Freedman, Room 308 

• Research Areas: Distributed systems, security, networking
• Projects related to streaming data analysis, datacenter systems and networks, untrusted cloud storage and applications. Please see my group website at http://sns.cs.princeton.edu/ for current research projects.

Ruth Fong, Room 032

• Research Areas: computer vision, machine learning, deep learning, interpretability, explainable AI, fairness and bias in AI
• Develop a technique for understanding AI models
• Design a AI model that is interpretable by design
• Build a paradigm for detecting and/or correcting failure points in an AI model
• Analyze an existing AI model and/or dataset to better understand its failure points
• Build a computer vision system for another domain (e.g., medical imaging, satellite data, etc.)
• Develop a software package for explainable AI
• Adapt explainable AI research to a consumer-facing problem

Note: I am happy to advise any project if there's a sufficient overlap in interest and/or expertise; please reach out via email to chat about project ideas.

Tom Griffiths, Room 405

Research areas: computational cognitive science, computational social science, machine learning and artificial intelligence

Note: I am open to projects that apply ideas from computer science to understanding aspects of human cognition in a wide range of areas, from decision-making to cultural evolution and everything in between. For example, we have current projects analyzing chess game data and magic tricks, both of which give us clues about how human minds work. Students who have expertise or access to data related to games, magic, strategic sports like fencing, or other quantifiable domains of human behavior feel free to get in touch.

Aarti Gupta, Room 220

• Research Areas: Formal methods, program analysis, logic decision procedures
• Finding bugs in open source software using automatic verification tools
• Software verification (program analysis, model checking, test generation)
• Decision procedures for logical reasoning (SAT solvers, SMT solvers)

Elad Hazan, Room 409  

• Research interests: machine learning methods and algorithms, efficient methods for mathematical optimization, regret minimization in games, reinforcement learning, control theory and practice
• Machine learning, efficient methods for mathematical optimization, statistical and computational learning theory, regret minimization in games.
• Implementation and algorithm engineering for control, reinforcement learning and robotics
• Implementation and algorithm engineering for time series prediction

Felix Heide, Room 410

• Research Areas: Computational Imaging, Computer Vision, Machine Learning (focus on Optimization and Approximate Inference).
• Optical Neural Networks
• Hardware-in-the-loop Holography
• Zero-shot and Simulation-only Learning
• Object recognition in extreme conditions
• 3D Scene Representations for View Generation and Inverse Problems
• Long-range Imaging in Scattering Media
• Hardware-in-the-loop Illumination and Sensor Optimization
• Inverse Lidar Design
• Phase Retrieval Algorithms
• Proximal Algorithms for Learning and Inference
• Domain-Specific Language for Optics Design

Kyle Jamieson, Room 306

• Research areas: Wireless and mobile networking; indoor radar and indoor localization; Internet of Things
• See other topics on my independent work  ideas page  (campus IP and CS dept. login req'd)

Alan Kaplan, 221 Nassau Street, Room 105

Research Areas:

• Random apps of kindness - mobile application/technology frameworks used to help individuals or communities; topic areas include, but are not limited to: first response, accessibility, environment, sustainability, social activism, civic computing, tele-health, remote learning, crowdsourcing, etc.
• Tools automating programming language interoperability - Java/C++, React Native/Java, etc.
• Software visualization tools for education
• Connected consumer devices, applications and protocols

Brian Kernighan, Room 311

• Research Areas: application-specific languages, document preparation, user interfaces, software tools, programming methodology
• Application-oriented languages, scripting languages.
• Tools; user interfaces
• Digital humanities

Zachary Kincaid, Room 219

• Research areas: programming languages, program analysis, program verification, automated reasoning
• Independent Research Topics:
• Develop a practical algorithm for an intractable problem (e.g., by developing practical search heuristics, or by reducing to, or by identifying a tractable sub-problem, ...).
• Design a domain-specific programming language, or prototype a new feature for an existing language.
• Any interesting project related to programming languages or logic.

Gillat Kol, Room 316

Aleksandra korolova, 309 sherrerd hall.

Available for single-term IW and senior thesis advising, 2023-2024

• Research areas: Societal impacts of algorithms and AI; privacy; fair and privacy-preserving machine learning; algorithm auditing.

Advisees typically have taken one or more of COS 226, COS 324, COS 423, COS 424 or COS 445.

Amit Levy, Room 307

• Research Areas: Operating Systems, Distributed Systems, Embedded Systems, Internet of Things
• Distributed hardware testing infrastructure
• Second factor security tokens
• Low-power wireless network protocol implementation
• USB device driver implementation

Kai Li, Room 321

• Research Areas: Distributed systems; storage systems; content-based search and data analysis of large datasets.
• Fast communication mechanisms for heterogeneous clusters.
• Approximate nearest-neighbor search for high dimensional data.
• Data analysis and prediction of in-patient medical data.
• Optimized implementation of classification algorithms on manycore processors.

Xiaoyan Li, 221 Nassau Street, Room 104

• Research areas: Information retrieval, novelty detection, question answering, AI, machine learning and data analysis.
• Explore new statistical retrieval models for document retrieval and question answering.
• Apply AI in various fields.
• Apply supervised or unsupervised learning in health, education, finance, and social networks, etc.
• Any interesting project related to AI, machine learning, and data analysis.

Wyatt Lloyd, Room 323

• Research areas: Distributed Systems
• Caching algorithms and implementations
• Storage systems
• Distributed transaction algorithms and implementations

Margaret Martonosi, Room 208

• Quantum Computing research, particularly related to architecture and compiler issues for QC.
• Computer architectures specialized for modern workloads (e.g., graph analytics, machine learning algorithms, mobile applications
• Investigating security and privacy vulnerabilities in computer systems, particularly IoT devices.
• Other topics in computer architecture or mobile / IoT systems also possible.

Jonathan Mayer, Sherrerd Hall, Room 307 

• Research areas: Technology law and policy, with emphasis on national security, criminal procedure, consumer privacy, network management, and online speech.
• Assessing the effects of government policies, both in the public and private sectors.
• Collecting new data that relates to government decision making, including surveying current business practices and studying user behavior.
• Developing new tools to improve government processes and offer policy alternatives.

Andrés Monroy-Hernández, Room 405

• Research Areas: Human-Computer Interaction, Social Computing, Public-Interest Technology, Augmented Reality, Urban Computing
• Research interests:developing public-interest socio-technical systems.  We are currently creating alternatives to gig work platforms that are more equitable for all stakeholders. For instance, we are investigating the socio-technical affordances necessary to support a co-op food delivery network owned and managed by workers and restaurants. We are exploring novel system designs that support self-governance, decentralized/federated models, community-centered data ownership, and portable reputation systems.  We have opportunities for students interested in human-centered computing, UI/UX design, full-stack software development, and qualitative/quantitative user research.
• Beyond our core projects, we are open to working on research projects that explore the use of emerging technologies, such as AR, wearables, NFTs, and DAOs, for creative and out-of-the-box applications.

Christopher Moretti, Corwin Hall, Room 036

• Research areas: Distributed systems, high-throughput computing, computer science/engineering education
• Expansion, improvement, and evaluation of open-source distributed computing software.
• Applications of distributed computing for "big science" (e.g. biometrics, data mining, bioinformatics)
• Software and best practices for computer science education and study, especially Princeton's 126/217/226 sequence or MOOCs development
• Sports analytics and/or crowd-sourced computing

Radhika Nagpal, F316 Engineering Quadrangle

• Research areas: control, robotics and dynamical systems

Karthik Narasimhan, Room 422

• Research areas: Natural Language Processing, Reinforcement Learning
• Autonomous agents for text-based games ( https://www.microsoft.com/en-us/research/project/textworld/ )
• Transfer learning/generalization in NLP
• Techniques for generating natural language
• Model-based reinforcement learning

Arvind Narayanan, 308 Sherrerd Hall 

Research Areas: fair machine learning (and AI ethics more broadly), the social impact of algorithmic systems, tech policy

Pedro Paredes, Corwin Hall, Room 041

My primary research work is in Theoretical Computer Science.

 * Research Interest: Spectral Graph theory, Pseudorandomness, Complexity theory, Coding Theory, Quantum Information Theory, Combinatorics.

The IW projects I am interested in advising can be divided into three categories:

 1. Theoretical research

I am open to advise work on research projects in any topic in one of my research areas of interest. A project could also be based on writing a survey given results from a few papers. Students should have a solid background in math (e.g., elementary combinatorics, graph theory, discrete probability, basic algebra/calculus) and theoretical computer science (226 and 240 material, like big-O/Omega/Theta, basic complexity theory, basic fundamental algorithms). Mathematical maturity is a must.

A (non exhaustive) list of topics of projects I'm interested in:   * Explicit constructions of better vertex expanders and/or unique neighbor expanders.   * Construction deterministic or random high dimensional expanders.   * Pseudorandom generators for different problems.   * Topics around the quantum PCP conjecture.   * Topics around quantum error correcting codes and locally testable codes, including constructions, encoding and decoding algorithms.

 2. Theory informed practical implementations of algorithms   Very often the great advances in theoretical research are either not tested in practice or not even feasible to be implemented in practice. Thus, I am interested in any project that consists in trying to make theoretical ideas applicable in practice. This includes coming up with new algorithms that trade some theoretical guarantees for feasible implementation yet trying to retain the soul of the original idea; implementing new algorithms in a suitable programming language; and empirically testing practical implementations and comparing them with benchmarks / theoretical expectations. A project in this area doesn't have to be in my main areas of research, any theoretical result could be suitable for such a project.

Some examples of areas of interest:   * Streaming algorithms.   * Numeric linear algebra.   * Property testing.   * Parallel / Distributed algorithms.   * Online algorithms.    3. Machine learning with a theoretical foundation

I am interested in projects in machine learning that have some mathematical/theoretical, even if most of the project is applied. This includes topics like mathematical optimization, statistical learning, fairness and privacy.

One particular area I have been recently interested in is in the area of rating systems (e.g., Chess elo) and applications of this to experts problems.

Final Note: I am also willing to advise any project with any mathematical/theoretical component, even if it's not the main one; please reach out via email to chat about project ideas.

Iasonas Petras, Corwin Hall, Room 033

• Research Areas: Information Based Complexity, Numerical Analysis, Quantum Computation.
• Prerequisites: Reasonable mathematical maturity. In case of a project related to Quantum Computation a certain familiarity with quantum mechanics is required (related courses: ELE 396/PHY 208).
• Possible research topics include:

1.   Quantum algorithms and circuits:

• i. Design or simulation quantum circuits implementing quantum algorithms.
• ii. Design of quantum algorithms solving/approximating continuous problems (such as Eigenvalue problems for Partial Differential Equations).

2.   Information Based Complexity:

• i. Necessary and sufficient conditions for tractability of Linear and Linear Tensor Product Problems in various settings (for example worst case or average case). 
• ii. Necessary and sufficient conditions for tractability of Linear and Linear Tensor Product Problems under new tractability and error criteria.
• iii. Necessary and sufficient conditions for tractability of Weighted problems.
• iv. Necessary and sufficient conditions for tractability of Weighted Problems under new tractability and error criteria.

3. Topics in Scientific Computation:

• i. Randomness, Pseudorandomness, MC and QMC methods and their applications (Finance, etc)

Yuri Pritykin, 245 Carl Icahn Lab

• Research interests: Computational biology; Cancer immunology; Regulation of gene expression; Functional genomics; Single-cell technologies.
• Potential research projects: Development, implementation, assessment and/or application of algorithms for analysis, integration, interpretation and visualization of multi-dimensional data in molecular biology, particularly single-cell and spatial genomics data.

Benjamin Raphael, Room 309  

• Research interests: Computational biology and bioinformatics; Cancer genomics; Algorithms and machine learning approaches for analysis of large-scale datasets
• Implementation and application of algorithms to infer evolutionary processes in cancer
• Identifying correlations between combinations of genomic mutations in human and cancer genomes
• Design and implementation of algorithms for genome sequencing from new DNA sequencing technologies
• Graph clustering and network anomaly detection, particularly using diffusion processes and methods from spectral graph theory

Vikram Ramaswamy, 035 Corwin Hall

• Research areas: Interpretability of AI systems, Fairness in AI systems, Computer vision.
• Constructing a new method to explain a model / create an interpretable by design model
• Analyzing a current model / dataset to understand bias within the model/dataset
• Proposing new fairness evaluations
• Proposing new methods to train to improve fairness
• Developing synthetic datasets for fairness / interpretability benchmarks
• Understanding robustness of models

Ran Raz, Room 240

• Research Area: Computational Complexity
• Independent Research Topics: Computational Complexity, Information Theory, Quantum Computation, Theoretical Computer Science

Szymon Rusinkiewicz, Room 406

• Research Areas: computer graphics; computer vision; 3D scanning; 3D printing; robotics; documentation and visualization of cultural heritage artifacts
• Research ways of incorporating rotation invariance into computer visiontasks such as feature matching and classification
• Investigate approaches to robust 3D scan matching
• Model and compensate for imperfections in 3D printing
• Given a collection of small mobile robots, apply control policies learned in simulation to the real robots.

Olga Russakovsky, Room 408

• Research Areas: computer vision, machine learning, deep learning, crowdsourcing, fairness&bias in AI
• Design a semantic segmentation deep learning model that can operate in a zero-shot setting (i.e., recognize and segment objects not seen during training)
• Develop a deep learning classifier that is impervious to protected attributes (such as gender or race) that may be erroneously correlated with target classes
• Build a computer vision system for the novel task of inferring what object (or part of an object) a human is referring to when pointing to a single pixel in the image. This includes both collecting an appropriate dataset using crowdsourcing on Amazon Mechanical Turk, creating a new deep learning formulation for this task, and running extensive analysis of both the data and the model

Sebastian Seung, Princeton Neuroscience Institute, Room 153

• Research Areas: computational neuroscience, connectomics, "deep learning" neural networks, social computing, crowdsourcing, citizen science
• Gamification of neuroscience (EyeWire  2.0)
• Semantic segmentation and object detection in brain images from microscopy
• Computational analysis of brain structure and function
• Neural network theories of brain function

Jaswinder Pal Singh, Room 324

• Research Areas: Boundary of technology and business/applications; building and scaling technology companies with special focus at that boundary; parallel computing systems and applications: parallel and distributed applications and their implications for software and architectural design; system software and programming environments for multiprocessors.
• Develop a startup company idea, and build a plan/prototype for it.
• Explore tradeoffs at the boundary of technology/product and business/applications in a chosen area.
• Study and develop methods to infer insights from data in different application areas, from science to search to finance to others. 
• Design and implement a parallel application. Possible areas include graphics, compression, biology, among many others. Analyze performance bottlenecks using existing tools, and compare programming models/languages.
• Design and implement a scalable distributed algorithm.

Mona Singh, Room 420

• Research Areas: computational molecular biology, as well as its interface with machine learning and algorithms.
• Whole and cross-genome methods for predicting protein function and protein-protein interactions.
• Analysis and prediction of biological networks.
• Computational methods for inferring specific aspects of protein structure from protein sequence data.
• Any other interesting project in computational molecular biology.

Robert Tarjan, 194 Nassau St., Room 308

Available for single-semester IW and senior thesis advising, 2022-2023

• Research Areas: Data structures; graph algorithms; combinatorial optimization; computational complexity; computational geometry; parallel algorithms.
• Implement one or more data structures or combinatorial algorithms to provide insight into their empirical behavior.
• Design and/or analyze various data structures and combinatorial algorithms.

Olga Troyanskaya, Room 320

• Research Areas: Bioinformatics; analysis of large-scale biological data sets (genomics, gene expression, proteomics, biological networks); algorithms for integration of data from multiple data sources; visualization of biological data; machine learning methods in bioinformatics.
• Implement and evaluate one or more gene expression analysis algorithm.
• Develop algorithms for assessment of performance of genomic analysis methods.
• Develop, implement, and evaluate visualization tools for heterogeneous biological data.

David Walker, Room 211

• Research Areas: Programming languages, type systems, compilers, domain-specific languages, software-defined networking and security
• Independent Research Topics:  Any other interesting project that involves humanitarian hacking, functional programming, domain-specific programming languages, type systems, compilers, software-defined networking, fault tolerance, language-based security, theorem proving, logic or logical frameworks.

Shengyi Wang, Postdoctoral Research Associate, Room 216

• Independent Research topics: Explore Escher-style tilings using (introductory) group theory and automata theory to produce beautiful pictures.

Kevin Wayne, Corwin Hall, Room 040

• Research Areas: design, analysis, and implementation of algorithms; data structures; combinatorial optimization; graphs and networks.
• Design and implement computer visualizations of algorithms or data structures.
• Develop pedagogical tools or programming assignments for the computer science curriculum at Princeton and beyond.
• Develop assessment infrastructure and assessments for MOOCs.

Matt Weinberg, 194 Nassau St., Room 222

• Research Areas: algorithms, algorithmic game theory, mechanism design, game theoretical problems in {Bitcoin, networking, healthcare}.
• Theoretical questions related to COS 445 topics such as matching theory, voting theory, auction design, etc. 
• Theoretical questions related to incentives in applications like Bitcoin, the Internet, health care, etc. In a little bit more detail: protocols for these systems are often designed assuming that users will follow them. But often, users will actually be strictly happier to deviate from the intended protocol. How should we reason about user behavior in these protocols? How should we design protocols in these settings?

Huacheng Yu, Room 310

• data structures
• streaming algorithms
• design and analyze data structures / streaming algorithms
• prove impossibility results (lower bounds)
• implement and evaluate data structures / streaming algorithms

Ellen Zhong, Room 314

No longer available for single-term IW  and senior thesis advising, 2023-2024

Opportunities outside the department

We encourage students to look in to doing interdisciplinary computer science research and to work with professors in departments other than computer science.  However, every CS independent work project must have a strong computer science element (even if it has other scientific or artistic elements as well.)  To do a project with an adviser outside of computer science you must have permission of the department.  This can be accomplished by having a second co-adviser within the computer science department or by contacting the independent work supervisor about the project and having he or she sign the independent work proposal form.

Here is a list of professors outside the computer science department who are eager to work with computer science undergraduates.

Maria Apostolaki, Engineering Quadrangle, C330

• Research areas: Computing & Networking, Data & Information Science, Security & Privacy

Branko Glisic, Engineering Quadrangle, Room E330

• Documentation of historic structures
• Cyber physical systems for structural health monitoring
• Developing virtual and augmented reality applications for documenting structures
• Applying machine learning techniques to generate 3D models from 2D plans of buildings
•  Contact : Rebecca Napolitano, rkn2 (@princeton.edu)

Mihir Kshirsagar, Sherrerd Hall, Room 315

Center for Information Technology Policy.

• Consumer protection
• Content regulation
• Competition law
• Economic development
• Surveillance and discrimination

Sharad Malik, Engineering Quadrangle, Room B224

Select a Senior Thesis Adviser for the 2020-21 Academic Year.

• Design of reliable hardware systems
• Verifying complex software and hardware systems

Prateek Mittal, Engineering Quadrangle, Room B236

• Internet security and privacy 
• Social Networks
• Privacy technologies, anonymous communication
• Network Science
• Internet security and privacy: The insecurity of Internet protocols and services threatens the safety of our critical network infrastructure and billions of end users. How can we defend end users as well as our critical network infrastructure from attacks?
• Trustworthy social systems: Online social networks (OSNs) such as Facebook, Google+, and Twitter have revolutionized the way our society communicates. How can we leverage social connections between users to design the next generation of communication systems?
• Privacy Technologies: Privacy on the Internet is eroding rapidly, with businesses and governments mining sensitive user information. How can we protect the privacy of our online communications? The Tor project (https://www.torproject.org/) is a potential application of interest.

Ken Norman,  Psychology Dept, PNI 137

• Research Areas: Memory, the brain and computation 
• Lab:  Princeton Computational Memory Lab

Potential research topics

• Methods for decoding cognitive state information from neuroimaging data (fMRI and EEG) 
• Neural network simulations of learning and memory

Caroline Savage

Office of Sustainability, Phone:(609)258-7513, Email: cs35 (@princeton.edu)

The  Campus as Lab  program supports students using the Princeton campus as a living laboratory to solve sustainability challenges. The Office of Sustainability has created a list of campus as lab research questions, filterable by discipline and topic, on its  website .

An example from Computer Science could include using  TigerEnergy , a platform which provides real-time data on campus energy generation and consumption, to study one of the many energy systems or buildings on campus. Three CS students used TigerEnergy to create a  live energy heatmap of campus .

Other potential projects include:

• Apply game theory to sustainability challenges
• Develop a tool to help visualize interactions between complex campus systems, e.g. energy and water use, transportation and storm water runoff, purchasing and waste, etc.
• How can we learn (in aggregate) about individuals’ waste, energy, transportation, and other behaviors without impinging on privacy?

Janet Vertesi, Sociology Dept, Wallace Hall, Room 122

• Research areas: Sociology of technology; Human-computer interaction; Ubiquitous computing.
• Possible projects: At the intersection of computer science and social science, my students have built mixed reality games, produced artistic and interactive installations, and studied mixed human-robot teams, among other projects.

David Wentzlaff, Engineering Quadrangle, Room 228

Computing, Operating Systems, Sustainable Computing.

• Instrument Princeton's Green (HPCRC) data center
• Investigate power utilization on an processor core implemented in an FPGA
• Dismantle and document all of the components in modern electronics. Invent new ways to build computers that can be recycled easier.
• Other topics in parallel computer architecture or operating systems

• USF Research
• USF Libraries

Digital Commons @ USF > College of Engineering > Computer Science and Engineering > Theses and Dissertations

Computer Science and Engineering Theses and Dissertations

Theses/dissertations from 2023 2023.

Refining the Machine Learning Pipeline for US-based Public Transit Systems , Jennifer Adorno

Insect Classification and Explainability from Image Data via Deep Learning Techniques , Tanvir Hossain Bhuiyan

Brain-Inspired Spatio-Temporal Learning with Application to Robotics , Thiago André Ferreira Medeiros

Evaluating Methods for Improving DNN Robustness Against Adversarial Attacks , Laureano Griffin

Analyzing Multi-Robot Leader-Follower Formations in Obstacle-Laden Environments , Zachary J. Hinnen

Secure Lightweight Cryptographic Hardware Constructions for Deeply Embedded Systems , Jasmin Kaur

A Psychometric Analysis of Natural Language Inference Using Transformer Language Models , Antonio Laverghetta Jr.

Graph Analysis on Social Networks , Shen Lu

Deep Learning-based Automatic Stereology for High- and Low-magnification Images , Hunter Morera

Deciphering Trends and Tactics: Data-driven Techniques for Forecasting Information Spread and Detecting Coordinated Campaigns in Social Media , Kin Wai Ng Lugo

Automated Approaches to Enable Innovative Civic Applications from Citizen Generated Imagery , Hye Seon Yi

Theses/Dissertations from 2022 2022

Towards High Performing and Reliable Deep Convolutional Neural Network Models for Typically Limited Medical Imaging Datasets , Kaoutar Ben Ahmed

Task Progress Assessment and Monitoring Using Self-Supervised Learning , Sainath Reddy Bobbala

Towards More Task-Generalized and Explainable AI Through Psychometrics , Alec Braynen

A Multiple Input Multiple Output Framework for the Automatic Optical Fractionator-based Cell Counting in Z-Stacks Using Deep Learning , Palak Dave

On the Reliability of Wearable Sensors for Assessing Movement Disorder-Related Gait Quality and Imbalance: A Case Study of Multiple Sclerosis , Steven Díaz Hernández

Securing Critical Cyber Infrastructures and Functionalities via Machine Learning Empowered Strategies , Tao Hou

Social Media Time Series Forecasting and User-Level Activity Prediction with Gradient Boosting, Deep Learning, and Data Augmentation , Fred Mubang

A Study of Deep Learning Silhouette Extractors for Gait Recognition , Sneha Oladhri

Analyzing Decision-making in Robot Soccer for Attacking Behaviors , Justin Rodney

Generative Spatio-Temporal and Multimodal Analysis of Neonatal Pain , Md Sirajus Salekin

Secure Hardware Constructions for Fault Detection of Lattice-based Post-quantum Cryptosystems , Ausmita Sarker

Adaptive Multi-scale Place Cell Representations and Replay for Spatial Navigation and Learning in Autonomous Robots , Pablo Scleidorovich

Predicting the Number of Objects in a Robotic Grasp , Utkarsh Tamrakar

Humanoid Robot Motion Control for Ramps and Stairs , Tommy Truong

Preventing Variadic Function Attacks Through Argument Width Counting , Brennan Ward

Theses/Dissertations from 2021 2021

Knowledge Extraction and Inference Based on Visual Understanding of Cooking Contents , Ahmad Babaeian Babaeian Jelodar

Efficient Post-Quantum and Compact Cryptographic Constructions for the Internet of Things , Rouzbeh Behnia

Efficient Hardware Constructions for Error Detection of Post-Quantum Cryptographic Schemes , Alvaro Cintas Canto

Using Hyper-Dimensional Spanning Trees to Improve Structure Preservation During Dimensionality Reduction , Curtis Thomas Davis

Design, Deployment, and Validation of Computer Vision Techniques for Societal Scale Applications , Arup Kanti Dey

AffectiveTDA: Using Topological Data Analysis to Improve Analysis and Explainability in Affective Computing , Hamza Elhamdadi

Automatic Detection of Vehicles in Satellite Images for Economic Monitoring , Cole Hill

Analysis of Contextual Emotions Using Multimodal Data , Saurabh Hinduja

Data-driven Studies on Social Networks: Privacy and Simulation , Yasanka Sameera Horawalavithana

Automated Identification of Stages in Gonotrophic Cycle of Mosquitoes Using Computer Vision Techniques , Sherzod Kariev

Exploring the Use of Neural Transformers for Psycholinguistics , Antonio Laverghetta Jr.

Secure VLSI Hardware Design Against Intellectual Property (IP) Theft and Cryptographic Vulnerabilities , Matthew Dean Lewandowski

Turkic Interlingua: A Case Study of Machine Translation in Low-resource Languages , Jamshidbek Mirzakhalov

Automated Wound Segmentation and Dimension Measurement Using RGB-D Image , Chih-Yun Pai

Constructing Frameworks for Task-Optimized Visualizations , Ghulam Jilani Abdul Rahim Quadri

Trilateration-Based Localization in Known Environments with Object Detection , Valeria M. Salas Pacheco

Recognizing Patterns from Vital Signs Using Spectrograms , Sidharth Srivatsav Sribhashyam

Recognizing Emotion in the Wild Using Multimodal Data , Shivam Srivastava

A Modular Framework for Multi-Rotor Unmanned Aerial Vehicles for Military Operations , Dante Tezza

Human-centered Cybersecurity Research — Anthropological Findings from Two Longitudinal Studies , Anwesh Tuladhar

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy , Troi André Williams

Human-centric Cybersecurity Research: From Trapping the Bad Guys to Helping the Good Ones , Armin Ziaie Tabari

Theses/Dissertations from 2020 2020

Classifying Emotions with EEG and Peripheral Physiological Data Using 1D Convolutional Long Short-Term Memory Neural Network , Rupal Agarwal

Keyless Anti-Jamming Communication via Randomized DSSS , Ahmad Alagil

Active Deep Learning Method to Automate Unbiased Stereology Cell Counting , Saeed Alahmari

Composition of Atomic-Obligation Security Policies , Yan Cao Albright

Action Recognition Using the Motion Taxonomy , Maxat Alibayev

Sentiment Analysis in Peer Review , Zachariah J. Beasley

Spatial Heterogeneity Utilization in CT Images for Lung Nodule Classication , Dmitrii Cherezov

Feature Selection Via Random Subsets Of Uncorrelated Features , Long Kim Dang

Unifying Security Policy Enforcement: Theory and Practice , Shamaria Engram

PsiDB: A Framework for Batched Query Processing and Optimization , Mehrad Eslami

Composition of Atomic-Obligation Security Policies , Danielle Ferguson

Algorithms To Profile Driver Behavior From Zero-permission Embedded Sensors , Bharti Goel

The Efficiency and Accuracy of YOLO for Neonate Face Detection in the Clinical Setting , Jacqueline Hausmann

Beyond the Hype: Challenges of Neural Networks as Applied to Social Networks , Anthony Hernandez

Privacy-Preserving and Functional Information Systems , Thang Hoang

Managing Off-Grid Power Use for Solar Fueled Residences with Smart Appliances, Prices-to-Devices and IoT , Donnelle L. January

Novel Bit-Sliced In-Memory Computing Based VLSI Architecture for Fast Sobel Edge Detection in IoT Edge Devices , Rajeev Joshi

Edge Computing for Deep Learning-Based Distributed Real-time Object Detection on IoT Constrained Platforms at Low Frame Rate , Lakshmikavya Kalyanam

Establishing Topological Data Analysis: A Comparison of Visualization Techniques , Tanmay J. Kotha

Machine Learning for the Internet of Things: Applications, Implementation, and Security , Vishalini Laguduva Ramnath

System Support of Concurrent Database Query Processing on a GPU , Hao Li

Deep Learning Predictive Modeling with Data Challenges (Small, Big, or Imbalanced) , Renhao Liu

Countermeasures Against Various Network Attacks Using Machine Learning Methods , Yi Li

Towards Safe Power Oversubscription and Energy Efficiency of Data Centers , Sulav Malla

Design of Support Measures for Counting Frequent Patterns in Graphs , Jinghan Meng

Automating the Classification of Mosquito Specimens Using Image Processing Techniques , Mona Minakshi

Models of Secure Software Enforcement and Development , Hernan M. Palombo

Functional Object-Oriented Network: A Knowledge Representation for Service Robotics , David Andrés Paulius Ramos

Lung Nodule Malignancy Prediction from Computed Tomography Images Using Deep Learning , Rahul Paul

Algorithms and Framework for Computing 2-body Statistics on Graphics Processing Units , Napath Pitaksirianan

Efficient Viewshed Computation Algorithms On GPUs and CPUs , Faisal F. Qarah

Relational Joins on GPUs for In-Memory Database Query Processing , Ran Rui

Micro-architectural Countermeasures for Control Flow and Misspeculation Based Software Attacks , Love Kumar Sah

Efficient Forward-Secure and Compact Signatures for the Internet of Things (IoT) , Efe Ulas Akay Seyitoglu

Detecting Symptoms of Chronic Obstructive Pulmonary Disease and Congestive Heart Failure via Cough and Wheezing Sounds Using Smart-Phones and Machine Learning , Anthony Windmon

Toward Culturally Relevant Emotion Detection Using Physiological Signals , Khadija Zanna

Theses/Dissertations from 2019 2019

Beyond Labels and Captions: Contextualizing Grounded Semantics for Explainable Visual Interpretation , Sathyanarayanan Narasimhan Aakur

Empirical Analysis of a Cybersecurity Scoring System , Jaleel Ahmed

Phenomena of Social Dynamics in Online Games , Essa Alhazmi

A Machine Learning Approach to Predicting Community Engagement on Social Media During Disasters , Adel Alshehri

Interactive Fitness Domains in Competitive Coevolutionary Algorithm , ATM Golam Bari

Measuring Influence Across Social Media Platforms: Empirical Analysis Using Symbolic Transfer Entropy , Abhishek Bhattacharjee

A Communication-Centric Framework for Post-Silicon System-on-chip Integration Debug , Yuting Cao

Authentication and SQL-Injection Prevention Techniques in Web Applications , Cagri Cetin

Multimodal Emotion Recognition Using 3D Facial Landmarks, Action Units, and Physiological Data , Diego Fabiano

Robotic Motion Generation by Using Spatial-Temporal Patterns from Human Demonstrations , Yongqiang Huang

A GPU-Based Framework for Parallel Spatial Indexing and Query Processing , Zhila Nouri Lewis

A Flexible, Natural Deduction, Automated Reasoner for Quick Deployment of Non-Classical Logic , Trisha Mukhopadhyay

An Efficient Run-time CFI Check for Embedded Processors to Detect and Prevent Control Flow Based Attacks , Srivarsha Polnati

Force Feedback and Intelligent Workspace Selection for Legged Locomotion Over Uneven Terrain , John Rippetoe

Detecting Digitally Forged Faces in Online Videos , Neilesh Sambhu

Malicious Manipulation in Service-Oriented Network, Software, and Mobile Systems: Threats and Defenses , Dakun Shen

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Home > FACULTIES > Computer Science > CSD-ETD

Computer Science Theses and Dissertations

This collection contains theses and dissertations from the Department of Computer Science, collected from the Scholarship@Western Electronic Thesis and Dissertation Repository

Theses/Dissertations from 2024 2024

A Target-Based and A Targetless Extrinsic Calibration Methods for Thermal Camera and 3D LiDAR , Farhad Dalirani

Investigating Tree- and Graph-based Neural Networks for Natural Language Processing Applications , Sudipta Singha Roy

Theses/Dissertations from 2023 2023

Classification of DDoS Attack with Machine Learning Architectures and Exploratory Analysis , Amreen Anbar

Multi-view Contrastive Learning for Unsupervised Domain Adaptation in Brain-Computer Interfaces , Sepehr Asgarian

Improved Protein Sequence Alignments Using Deep Learning , Seyed Sepehr Ashrafzadeh

INVESTIGATING IMPROVEMENTS TO MESH INDEXING , Anurag Bhattacharjee

Algorithms and Software for Oligonucleotide Design , Qin Dong

Framework for Assessing Information System Security Posture Risks , Syed Waqas Hamdani

De novo sequencing of multiple tandem mass spectra of peptide containing SILAC labeling , Fang Han

Local Model Agnostic XAI Methodologies Applied to Breast Cancer Malignancy Predictions , Heather Hartley

A Quantitative Analysis Between Software Quality Posture and Bug-fixing Commit , Rongji He

A Novel Method for Assessment of Batch Effect on single cell RNA sequencing data , Behnam Jabbarizadeh

Dynamically Finding Optimal Kernel Launch Parameters for CUDA Programs , Taabish Jeshani

Citation Polarity Identification From Scientific Articles Using Deep Learning Methods , Souvik Kundu

Denoising-Based Domain Adaptation Network for EEG Source Imaging , Runze Li

Decoy-Target Database Strategy and False Discovery Rate Analysis for Glycan Identification , Xiaoou Li

DpNovo: A DEEP LEARNING MODEL COMBINED WITH DYNAMIC PROGRAMMING FOR DE NOVO PEPTIDE SEQUENCING , Yizhou Li

Developing A Smart Home Surveillance System Using Autonomous Drones , Chongju Mai

Look-Ahead Selective Plasticity for Continual Learning , Rouzbeh Meshkinnejad

The Two Visual Processing Streams Through The Lens Of Deep Neural Networks , Aidasadat Mirebrahimi Tafreshi

Source-free Domain Adaptation for Sleep Stage Classification , Yasmin Niknam

Data Heterogeneity and Its Implications for Fairness , Ghazaleh Noroozi

Enhancing Urban Life: A Policy-Based Autonomic Smart City Management System for Efficient, Sustainable, and Self-Adaptive Urban Environments , Elham Okhovat

Evaluating the Likelihood of Bug Inducing Commits Using Metrics Trend Analysis , Parul Parul

On Computing Optimal Repairs for Conditional Independence , Alireza Pirhadi

Open-Set Source-Free Domain Adaptation in Fundus Images Analysis , Masoud Pourreza

Migration in Edge Computing , Arshin Rezazadeh

A Modified Hopfield Network for the K-Median Problem , Cody Rossiter

Predicting Network Failures with AI Techniques , Chandrika Saha

Toward Building an Intelligent and Secure Network: An Internet Traffic Forecasting Perspective , Sajal Saha

An Exploration of Visual Analytic Techniques for XAI: Applications in Clinical Decision Support , Mozhgan Salimiparsa

Attention-based Multi-Source-Free Domain Adaptation for EEG Emotion Recognition , Amir Hesam Salimnia

Global Cyber Attack Forecast using AI Techniques , Nusrat Kabir Samia

IMPLEMENTATION OF A PRE-ASSESSMENT MODULE TO IMPROVE THE INITIAL PLAYER EXPERIENCE USING PREVIOUS GAMING INFORMATION , Rafael David Segistan Canizales

A Computational Framework For Identifying Relevant Cell Types And Specific Regulatory Mechanisms In Schizophrenia Using Data Integration Methods , Kayvan Shabani

Weakly-Supervised Anomaly Detection in Surveillance Videos Based on Two-Stream I3D Convolution Network , Sareh Soltani Nejad

Smartphone Loss Prevention System Using BLE and GPS Technology , Noshin Tasnim

A Hybrid Continual Machine Learning Model for Efficient Hierarchical Classification of Domain-Specific Text in The Presence of Class Overlap (Case Study: IT Support Tickets) , Yasmen M. Wahba

Reducing Negative Transfer of Random Data in Source-Free Unsupervised Domain Adaptation , Anthony Wong

Deep Neural Methods for True/Pseudo- Invasion Classification in Colorectal Polyp Whole-Slide Images , Zhiyuan Yang

Developing a Relay-based Autonomous Drone Delivery System , Muhammad Zakar

Learning Mortality Risk for COVID-19 Using Machine Learning and Statistical Methods , Shaoshi Zhang

Machine Learning Techniques for Improved Functional Brain Parcellation , Da Zhi

Theses/Dissertations from 2022 2022

The Design and Implementation of a High-Performance Polynomial System Solver , Alexander Brandt

Defining Service Level Agreements in Serverless Computing , Mohamed Elsakhawy

Algorithms for Regular Chains of Dimension One , Juan P. Gonzalez Trochez

Towards a Novel and Intelligent e-commerce Framework for Smart-Shopping Applications , Susmitha Hanumanthu

Multi-Device Data Analysis for Fault Localization in Electrical Distribution Grids , Jacob D L Hunte

Towards Parking Lot Occupancy Assessment Using Aerial Imagery and Computer Vision , John Jewell

Potential of Vision Transformers for Advanced Driver-Assistance Systems: An Evaluative Approach , Andrew Katoch

Psychological Understanding of Textual journals using Natural Language Processing approaches , Amirmohammad Kazemeinizadeh

Driver Behavior Analysis Based on Real On-Road Driving Data in the Design of Advanced Driving Assistance Systems , Nima Khairdoost

Solving Challenges in Deep Unsupervised Methods for Anomaly Detection , Vahid Reza Khazaie

Developing an Efficient Real-Time Terrestrial Infrastructure Inspection System Using Autonomous Drones and Deep Learning , Marlin Manka

Predictive Modelling For Topic Handling Of Natural Language Dialogue With Virtual Agents , Lareina Milambiling

Improving Deep Entity Resolution by Constraints , Soudeh Nilforoushan

Respiratory Pattern Analysis for COVID-19 Digital Screening Using AI Techniques , Annita Tahsin Priyoti

Extracting Microservice Dependencies Using Log Analysis , Andres O. Rodriguez Ishida

False Discovery Rate Analysis for Glycopeptide Identification , Shun Saito

Towards a Generalization of Fulton's Intersection Multiplicity Algorithm , Ryan Sandford

An Investigation Into Time Gazed At Traffic Objects By Drivers , Kolby R. Sarson

Exploring Artificial Intelligence (AI) Techniques for Forecasting Network Traffic: Network QoS and Security Perspectives , Ibrahim Mohammed Sayem

A Unified Representation and Deep Learning Architecture for Persuasive Essays in English , Muhammad Tawsif Sazid

Towards the development of a cost-effective Image-Sensing-Smart-Parking Systems (ISenSmaP) , Aakriti Sharma

Advances in the Automatic Detection of Optimization Opportunities in Computer Programs , Delaram Talaashrafi

Reputation-Based Trust Assessment of Transacting Service Components , Konstantinos Tsiounis

Fully Autonomous UAV Exploration in Confined and Connectionless Environments , Kirk P. Vander Ploeg

Three Contributions to the Theory and Practice of Optimizing Compilers , Linxiao Wang

Developing Intelligent Routing Algorithm over SDN: Reusable Reinforcement Learning Approach , Wumian Wang

Predicting and Modifying Memorability of Images , Mohammad Younesi

Theses/Dissertations from 2021 2021

Generating Effective Sentence Representations: Deep Learning and Reinforcement Learning Approaches , Mahtab Ahmed

A Physical Layer Framework for a Smart City Using Accumulative Bayesian Machine Learning , Razan E. AlFar

Load Balancing and Resource Allocation in Smart Cities using Reinforcement Learning , Aseel AlOrbani

Contrastive Learning of Auditory Representations , Haider Al-Tahan

Cache-Friendly, Modular and Parallel Schemes For Computing Subresultant Chains , Mohammadali Asadi

Protein Interaction Sites Prediction using Deep Learning , Sourajit Basak

Predicting Stock Market Sector Sentiment Through News Article Based Textual Analysis , William A. Beldman

Improving Reader Motivation with Machine Learning , Tanner A. Bohn

A Black-box Approach for Containerized Microservice Monitoring in Fog Computing , Shi Chang

Visualization and Interpretation of Protein Interactions , Dipanjan Chatterjee

A Framework for Characterising Performance in Multi-Class Classification Problems with Applications in Cancer Single Cell RNA Sequencing , Erik R. Christensen

Exploratory Search with Archetype-based Language Models , Brent D. Davis

Evolutionary Design of Search and Triage Interfaces for Large Document Sets , Jonathan A. Demelo

Building Effective Network Security Frameworks using Deep Transfer Learning Techniques , Harsh Dhillon

A Deep Topical N-gram Model and Topic Discovery on COVID-19 News and Research Manuscripts , Yuan Du

Automatic extraction of requirements-related information from regulatory documents cited in the project contract , Sara Fotouhi

Developing a Resource and Energy Efficient Real-time Delivery Scheduling Framework for a Network of Autonomous Drones , Gopi Gugan

A Visual Analytics System for Rapid Sensemaking of Scientific Documents , Amirreza Haghverdiloo Barzegar

Calibration Between Eye Tracker and Stereoscopic Vision System Employing a Linear Closed-Form Perspective-n-Point (PNP) Algorithm , Mohammad Karami

Fuzzy and Probabilistic Rule-Based Approaches to Identify Fault Prone Files , Piyush Kumar Korlepara

Parallel Arbitrary-precision Integer Arithmetic , Davood Mohajerani

A Technique for Evaluating the Health Status of a Software Module Using Process Metrics , . Ria

Visual Analytics for Performing Complex Tasks with Electronic Health Records , Neda Rostamzadeh

Predictive Model of Driver's Eye Fixation for Maneuver Prediction in the Design of Advanced Driving Assistance Systems , Mohsen Shirpour

A Generative-Discriminative Approach to Human Brain Mapping , Deepanshu Wadhwa

WesternAccelerator：Rapid Development of Microservices , Haoran Wei

A Lightweight and Explainable Citation Recommendation System , Juncheng Yin

Mitosis Detection from Pathology Images , Jinhang Zhang

Theses/Dissertations from 2020 2020

Visual Analytics of Electronic Health Records with a focus on Acute Kidney Injury , Sheikh S. Abdullah

Towards the Development of Network Service Cost Modeling-An ISP Perspective , Yasmeen Ali

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©1878 - 2016 Western University

• © 2008

Thesis Projects

A Guide for Students in Computer Science and Information Systems

• Mikael Berndtsson 0 ,
• Jörgen Hansson 1 ,
• Björn Olsson 2 ,
• Björn Lundell 3

University of Skövde, Sweden

You can also search for this author in PubMed   Google Scholar

Carnegie Mellon University, Pittsburgh, USA

• Provides a comprehensive approach to tackling project work
• Offers a simple step-by-step guide to the key processes involved
• Includes supplementary material: sn.pub/extras

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Table of contents (15 chapters)

Front matter, introduction, computer science and information systems research projects, actors involved, their roles and relationships, the process – an overview, developing your project proposal, references and citations, developing your aim, developing your objectives and choosing methods, following the objectives, presenting and analysing your data, drawing your conclusions and identifying future work, presenting and defending your work orally, supplements, information-seeking and use, examination, back matter.

• Collaboration
• Information Systems
• Project Work and Education
• Virtual Environments
• information technology

Mikael Berndtsson, Björn Olsson, Björn Lundell

Jörgen Hansson

Book Title : Thesis Projects

Book Subtitle : A Guide for Students in Computer Science and Information Systems

Authors : Mikael Berndtsson, Jörgen Hansson, Björn Olsson, Björn Lundell

DOI : https://doi.org/10.1007/978-1-84800-009-4

Publisher : Springer London

eBook Packages : Computer Science , Computer Science (R0)

Copyright Information : Springer-Verlag London 2008

Softcover ISBN : 978-1-84800-008-7 Published: 25 October 2007

eBook ISBN : 978-1-84800-009-4 Published: 30 October 2007

Edition Number : 2

Number of Pages : XIV, 162

Number of Illustrations : 25 b/w illustrations

Topics : Computer Science, general

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IT & Computer Science THESIS AND RESEARCH TOPICS

Information technology (IT) and computer science research topics propel the digital age and landscape, shaping AI, cybersecurity, and user-friendly interfaces to revolutionize industries, societies, and human experiences. View all our IT and computer science thesis topics below.

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Select academic degrees to find inspiration from.

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Overview of IT & Computer Science topics for bachelor and master thesis project

Find IT and computer science research topics and themes in artificial intelligence (AI), machine learning (ML), IT security, software engineering, data science, UX/UI, NLP, app development, human-computer interaction (HCI), and much more! Be inspired on your tech journey here.

• University of Southern Denmark
• Master of Science
• Spring 2024

IT & Computer Science

Design Innovation

Design research

Product innovation

User experiences on play

Research on experiences

Exploring the Lived Experience of Play: A Phenomenological Inquiry

How play is experienced and what the implications are for design.

The act of play is a fundamental aspect of human life, influencing various domains such as creativity, social interaction, well-being, and personal development. Despite its ubiquity, the subjective nature of play remains relatively unexplored. This research proposes a phenomenological inquiry into the lived experiences of play, aiming to uncover the intricate ways individuals engage with and perceive play in diverse contexts.   Background and Rationale:   Play encompasses a wide ra...

1 x Cand.it. i Produkt Design

• University of Copenhagen

Quantum Computing

Climate Modeling

Environmental Simulation

Algorithm Development

Data Analysis in Climate Science

Leveraging Quantum Computing for Enhanced Climate Modeling and Simulation

Harnessing Quantum Power for Climate Insights: A New Era in Environmental Modeling

Introduction With its ability to solve complex computational problems more efficiently than classical computing, quantum computing has emerged as a promising field. This thesis presents an opportunity to explore the application of quantum computing in the crucial domain of climate modeling and simulation. By developing and assessing quantum-enhanced models, we can achieve more accurate predictions of weather patterns, ocean currents, and the impact of greenhouse gases. This research has the pote...

1 x MSc in Computer Science

Digital Healthcare

Patient-Clinic Communication

Medical Data Security

Healthcare Mobile Application

Universal Patient-Clinic Communication Application

Overview  The proposed thesis focuses on developing a comprehensive application designed to streamline and enhance communication between patients and clinics. This multifunctional platform aims to cover all aspects of medical interaction, from appointment booking to surgery scheduling. It will facilitate the maintenance of digital medical records, including receipts and reports like scans and X-rays, ensuring transparency and accessibility for patients. Motivation: The primary motivation be...

Cybersecurity

Energy Consumption

IoT Architecture

Optimizing IoT Efficiency: Enhancing Performance While Ensuring Security

Advancing Energy-Efficient and Secure IoT Solutions: A Collaborative Research Initiative

In the era of digital transformation, the Internet of Things (IoT) stands as a cornerstone of innovation and efficiency. Our research project, titled "Optimizing IoT Efficiency: Enhancing Performance While Ensuring Security," aims to advance the standards of operational efficiency and security in IoT systems. Our thesis project will conduct an in-depth evaluation of your current IoT system architecture, focusing on optimizing energy usage while maintaining effective security. By dissecting the i...

1 x Cybersecurity

• Aalborg University

User Experience

Machine Learning

Digital Product Design

Data-driven Insights

User-Centered Design

Crafting Exceptional User Experiences: A Data-Driven Approach to Digital Product Design

Enhancing User Experience, Fostering Innovation, and Guiding Informed Decision-Making in Digital Product Development

Introduction  In today's dynamic digital landscape, organizations spanning diverse sectors face an ongoing challenge: the continuous enhancement of user experience (UX) and innovation in their digital products and services. This thesis proposal presents a dynamic framework that seamlessly merges user-centred design principles with data-driven insights, enhanced by machine learning, with a sharp focus on elevating UX and stimulating product innovation. This proposal outlines an adaptable fra...

1 x MSc in Information Science (Information Studies)

1 x Cand.it. i Information Science (Information Studies)

• Aarhus University

Cyber Security

Business Development

Cyber Security Strategies in an AI Generation

The unique challenges SME's face in securing their digital assets and data, and how they can implement robust security protocols in an AI generation.

This thesis will investigate practical, scalable cybersecurity strategies for small and medium-sized enterprises (SMEs). Recognizing the unique challenges SMEs face, such as limited budgets and expertise, the study will focus on identifying cybersecurity threats specific to SMEs and evaluating affordable, efficient security solutions with AI. The research will include a survey of current cybersecurity risks, an assessment of various security frameworks and tools suitable for SMEs, and interviews...

1 x Msc in Technology based Business Development

Optimization

Data Management

Education Sector

Optimization of Data Management and Compliance in the Education Sector through Chatbots

Enhancing Efficiency and Security with AI-Powered Solutions

I wish to examine how chatbots, powered by artificial intelligence (AI), can play a crucial role in optimizing data management and security compliance in the education sector. Chatbots have become increasingly sophisticated, and their potential in terms of data management and compliance is only beginning to be explored. The focus will be on key areas, such as the implementation of chatbots in the education sector, including how chatbots can be effectively integrated into the school's IT environm...

1 x Cand.it. i Webkommunikation

• Technical University of Denmark

Rsk assesment

Quantative analysis

Data analysis

Machine Learning in the Financial Sector

Risk management, portfolio optimization

Machine Learning Project in Finance  The main goal for our Master Project is to implement different machine learning algorithms (including reinforcement learning and deep learning) in finance. We are mainly interested in testing the performance of these algorithms (with comparison to available approaches) in: 1.     Risk Assessment - assessing and managing risks in investment portfolios 2.     Portfolio Optimization - using algorithms to construct diversified portfolios ...

1 x MSc in Engineering (Business Analytics)

IT-implementation

Project management

Change management

Data mangement

Process innovation

IT-implementation in company X

Streamlining processes through IT/data

How can technology or data contribute to streamlining the daily work in a company? And how can the company, through effective management, motivate the company to use the technology or data correct? This is what I want to examine in my master thesis. The company or organisation can be in the public or private sector in any given industry. A potential research question can be as following: "How can the organisation X use technology Y to streamline workflow, and which implication can appear during ...

1 x Cand.it. i IT, Kommunikation og Organisation (ITKO)

UI/UX Design

Website Redesign

Usability Enhancement

User-Centric Redesign

Graphic Design

UI/UX Design with a prototype

This thesis in website redesign would focus on the comprehensive overhaul and optimization of an existing website. This project would involve a deep analysis of the current website's user experience, design, functionality, and performance. The aim is to identify shortcomings and areas for improvement, taking into account user feedback and industry best practices. The thesis would propose and implement innovative design concepts, user interface enhancements, and potentially, the integration of cu...

Software Engineering

Agile Methodology

User-Centric Software Engineering Project

Leveraging agile principles and domain knowledge to deliver valueable software product

Are you looking for an eager collaboration partner to aid in the design, implementation and/or testing of a high-value software system? Does the project frame and scope lend itself to a thesis collaboration? Then I would be honored to assist! Ideally I am seeking an opportunity to contribute to a new or existing software project that places a strong emphasis on agile methodologies, user-centric development, and the utilization of contemporary technologies. While collaboration within a team is de...

1 x MSc in Engineering (Computer Science and Engineering)

• Copenhagen Business School

Data Science

Deep Learning

Machine Learning applied to business context

How ML can bring value

The idea is to identify Machine Learning techniques that are appropriate to the existing framework of the company and industry. The main steps of Data Science Methodology will be applied:  -       Data Preprocessing with a focus on handling missing values, outliers, and noise.  -       Exploratory Data Analysis in order to uncover patterns, correlations, and potential anomalies within the data. -       Model Development: unsupervised/supervi...

1 x MSc in Business Administration and Data Science

• Master of Arts

communication

Thesis in Communication & IT

Open for suggestions

Hello! We are three cand.IT students from Communication & IT at Københavns Universitet looking for someone to collaborate with on our master thesis. We have experience with: Analysing datasets Developing ideas to optimise workflows Design and innovation in relation to interfaces and IT-systems Previously, we have collaborated with several companies in relation to our education. We are open for suggestions on specific issues in your organisation or company, on which you could use some in...

1 x Cand.mag. i Kommunikation og IT

Innovative Solutions

Data Science Students

Efficiency Improvements

CSR related activities

Financial background

Open to Fine-Tune Solutions in Partnership with Your Company

We are two dedicated MSc students in Business Analytics and Data Science, seeking an collaboration with a company for our thesis project. About Us: - We both have a strong academic background in finance and economics - Our shared interests revolve around utilizing big data analytics, algorithms, and machine learning models to optimize processes and enhance workflows. - We are passionate about sustainability and Corporate Social Responsibility (CSR) initiatives. - Together, we have successfully c...

Mental Health Assessment

Adaptive Personalized Care

Conversational AI

Digital Therapeutic Interaction

Development and Implementation of an AI-Driven Mental Health Tool for Adaptive Patient Assessment and Psychiatrist Matching

Conversational AI x Mental Health

In the realm of healthcare, technology-driven solutions have become essential to assist patients, therapists, and support networks. In the context of mental health, where personalized care is paramount, the development of thoughtfully crafted technological tools is imperative. Individuals facing mental health challenges require solutions that align with their unique needs and capabilities. A well-designed user interface (UI) and an enriching user experience (UX) are critical for ensuring that th...

1 x MSc in Engineering (Human-Centered Artificial Intelligence)

• Roskilde University
• Spring 2023

Data prediction using different machine learning models

Computer science

The main focus of this project is to work with real life problems and real life data. As the title suggests, we are thinking of using different methods to predict new data....

1 x Computer Science and Informatics

Research Interest

AI in practice

Internatiol Network

Human-ML Augmentation

How to improve fairness when augmenting human decisions with Machine Learning

MIS Quarterly The thesis will investigate how Machine Learning influences excisting Information Systems theories and their notions of fairness in collaboration and decision making. Artificial Intelligence and Machine Learning is already widely used and will be applied even more in the future. Sometimes machines are taught human biases and even extend those on a larger scale, this needs to be prevented by creating models sensitive to fairness. However in other cases machines and algorithms can en...

1 x Business Administration and Information Systems

• IT University of Copenhagen

Reduced costs

Process optimisation

Process automatisation from manual to automatic

Automatisation of a process

We are three student from IT-University who are writing a bachelor project focusing on processes. We are looking for a process were we can automate manual tasks with creating, storing or moving data in excel or other easy-accesible systems. The benefit of this automatizion will unlock possibilities for Business Intelligence and increased usage of the data and/or simply heap the benefits of reduced costs....

1 x Global Business Informatics

IT transformation

Participatory IT Design

Preliminary study in IT transformation

In recent years a lot of organizations are looking towards IT to solve business and organizational related problems. This means a lot of time and money are spend on a variety of projects, some with more success than others. This project is preliminary study of such a situation. Using the MUST-method, the project examines the feasibility of a future or existing IT solution to a given problem. The MUST-method is a hollistic approah where all affected parties in the organization is included, and ar...

1 x Software Development

Algorithmic management

human vs. technological

Efficiency and optimization

Bachelor thesis: Algorithmic Management in organizations

Bachelor of science - Global Business Informatics

We are a group of three Global Business Informatics students at ITU, in the midst of our bachelor's project. We share an interest in technologies that form and co-construct in relation to organizational structures and in that regard wish to explore this further with our project.  We intend to investigate the shifts in organizing principles that take form in the presence of algorithmic management technologies. We find this topic interesting due to the multiple aspects it presents: human vs. ...

Design process

User centered

Creative approach

Collaboration

How UX can help solve user pain points

Use our UX and design process skills to help illuminate problems and suggest solutions

We haven't set our minds on a thesis topic yet, but would rather use Excelerate as an opportunity for inspiration through collaboration. We are interested in finding user pain points or problematics, and through data collecting and design processes try to solve this problematics - potentially with Hi-Fi prototype(s). We hope to find these problematics through a collaboration, discussion or/and conversation with you as our potential partner. We especially find interest within the field of AI (fro...

1 x Digital Design and Interactive Technologies

• Spring 2022

Ethical application

Better algorithms

Ethical applicationen of AI

How to make ethical algorithms

A while back an algorithm was implemented in jobcentres that predicted who were at risk for becoming long-term unemployed. When implemented it predicted that people above the age of 60 and those whose parents came from other countries were more likely to become unemployed. The algorithm did not solve a problem with unemployment, but instead just predicted the biases that employers have when they are looking to hire new employees.Instead an algorithm that focused on competences might have been mo...

1 x IT Management

Universities

Plagiarism Detection Systems

Evaluating the Efficacy of University Plagiarism Detection Systems in Verifying Student Authenticity of Knowledge in the Era of ChatGPT

Ensuring Academic Integrity in the Age of ChatGPT: An Assessment of University Plagiarism Detection Systems and their Effectiveness in Verifying Student Knowledge Authenticity

This thesis aims to evaluate the efficacy of plagiarism detection systems used by universities in verifying the authenticity of students' knowledge, specifically in the context of ChatGPT and similar AI models. By assessing the capabilities and limitations of these systems within the university environment, this research will explore whether they can effectively identify instances of plagiarism involving AI-generated content and ensure the authenticity of student work.  ...

decision-making

data science

Creating a business reporting app, as a method of quick response to threats

Nowadays proper information is crucial to achieve success - how coding can help us with it

My idea is to write about giving a proper information about e.g. amount of sold products to the team and managersd. My field of study is Data Science, so I want to create an app which will automate process of informing management about organisation's results. My idea is to begin why it is crucial to inform a team frequently and indroducing main methods to do so (including review literature and comparing different methods of doing it). Later my idea is to move to methodology where I will create a...

1 x MSc in Social Data Science

Mobile App Development

Application

Navigation App

Android Studio

Alternative way to indicate directions for the user

Mobile App development

My idea is to create an app that would direct a user from place A to B by giving vibration signals to the user.  The app would have a map on the interface and the user would insert where they want to go. Then the map would give signals by vibrating when the user needs to turn left or right.  I argue this idea would be useful for people cycling if they don't want to have a phone in their hand while they cycle. Also if you run on a new route and you don't want to stop and check direction...

Digital Design

User Insights

Prototyping

UX Design in Digital Development

A case study focusing on user involvement in digital development to improve user experiences

We are looking for a partner to collaborate with for our thesis, to investigate a concrete case where we can use our methodologies from UX Design and digital design in general. We have a philosophy that is based on the assumption that user involvement enhances the user experiences. ...

Artificial Intelligence

The Importance of Machine Learning algorithms in the Health Sector

We are two master students currently studying Business Administration and Data Science at Copenhagen Business School. At the moment, we are starting our final year and we are therefore looking for a partner for our master's thesis. We want to specialize in the field of Machine Learning with a focus on the health sector, which is why we are making this account. ...

1 x Business Administration and Data Science

Modern organization

Cyber security risks in the modern organization (working title)

How to handle cyber security risks in a modern organization and the economic consequences hereof

"43% of cyber attacks are aimed at small businesses, but only 14% are prepared to defend themselves" [1] is a shocking but important statistic. As the cyber threat keeps growing, the modern organization needs to be prepared, as ignoring these threats can cause financial and reputational damage. It is simply something that cannot be ignored. Recent events, such as the Covid-19 outbreak has caused an organizational change in many companies around the world. "Home office" or remote work has become ...

Design Thinking

Real word case

How could we improve a company’s product by using a design thinking approach

Dive into each step of the design thinking project and compare it to their processes

How can we improve a company’s product/processes by using a design thinking approach  ...

1 x Problem Based Learning in Engineering and Science

Business strategy

Deploying MLOps in a live production setup - a demo case study to operationalize machine learning

Deploying MLOps – the most pivotal but also underrated component in machine learning: A demo case study on [insert use case theme here]

Our thesis aims to operationalise a machine learning workflow for a company or department that is interested to deploy a machine learning solution to enhance their work. The theoretical underpinnings of this machine learning workflow (also referred to as MLOps) will be based on materials stemming from different courses – ranging from infrastructural choices (e.g. Microsoft Azure, Databricks, AWS etc.), database choice (e.g. RDMBS vs NoSQL), database design theories, reference architecture ...

machine learning

deep learning

data analysis

artificial intelligence

Master thesis within Machine Learning

Application and developement

Hello,I am studying for a master's in Human-centered AI at DTU. I am about to write my thesis next spring (starting around the 1st of February) and in that regard, I am exploring what exciting thesis options exist.Through both my bachelor's and master I have done a lot of different kinds of machine learning and I would thus like to find a thesis project within this area. I wish to write a thesis which both has a practical and theoretical aspect. The practical aspect could be a type of product, w...

Machine Learing

Neural Radiance Fields

Proven team

Neural Radiance Fields research and application

Research into expanding neural radiance fields and then applying it to the real world.

We are looking for a project A bachelor project centered around machine learning Specifically something within the field of deep learing, and we welcome you to propose any projects that could benefit from our set of skills. Currently, we have been looking at Neural Radiance Fields (NeRF) and its applications. It is a new technique that enables novel view synthesis from just a few images. This allows you to "fly" around a scene and see it from any direction. Specifically BaRF, Mip-NeRF 360, and I...

1 x Engineering (Artificial Intelligence and Data)

Risk Management

A Cybersecurity Risk-management Approach

NIS2-directive

Research Aim: The aim of the research is to investigate X's cyber risk management approach in relation to implementing and maintaining the NIS2-directive's minimum security measures to ensure high level security in EU....

Reading disorder

Helping regular people understand the life of dyslexic friends and family

A tool for helping relatives and interested parties to understand life with dyslexia

The thesis is currently marked as just 1 student but ideally I will find 1 or 2 more to join me on this endeavour. The core inspiration for this comes from the games and simulations intended to let typical people experience what it's like to have autism. An example of these would be Autismity. Dyslexia is generally treated less severely than for example autism and we already have various tools to aid dyslexic people deal with education and more, so providing a tool, game or simulation for actual...

Online Fraud

Banking Industry

Identity Theft

Combating Identity Theft and Fraud in Online Games

At present time, fraudsters flourishes in online communities. As a result, the banking industry and the Danish police experience a massive number of reports from victims of this type of crime. Dealing with this problem is important so that it can be safe and secure for the individual to shop online....

1 x MSc in Software Design

Find more thesis topics in related research areas

Looking for more thesis topic inspiration? Find topic ideas and examples in related research areas below.

19 Engineering & Technology

Interested in machines, algorithms, and structures that shape industries, societies, and our lives? Browse engineering and technology research topics that merge design, creativity, and innovation toward a smarter future.

Engineering & Technology research topics

7 sustainability & environment.

Interested in environmental dynamics and safeguarding our Planet? Explore research topics in environment, sustainability, and climate seeking to tackle climate change, cultivate sustainable practices, and craft greener, healthier solutions.

Sustainability & Environment research topics

2 chemistry.

Interested in our universe's building blocks, unlocking the secrets of chemical compositions and reactions? Explore chemistry research topics that delve into the world of atoms and molecules.

Chemistry research topics

1 mathematics & statistics.

Interested in the language of numbers, equations, and probabilities? Explore mathematical and statistical research topics digging into real-world puzzles that unravel complex data, patterns, and problems.

Mathematics & Statistics research topics

1 medicine & health.

Interested in the complexities of human well-being, from cellular mechanisms to healthcare systems? Explore medicine and health research topics delving into solutions for healthier societies.

Medicine & Health research topics

Interested in the complexities of the living world, from genes to ecosystems? Explore biology research topics that seek to enrich our understanding of medicine, conservation, and of life itself.

Biology research topics

0 astronomy.

Interesting in delving into the celestial mysteries, from stars and galaxies to the universe's grand narrative? Explore astronomy research topics on an astronomical journey to understand our universe's origin and evolution.

Astronomy research topics

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Related articles

Find the perfect thesis topic – 8 useful tips, how to write a thesis alone, thesis writing in a group, thesis writing tips – a guide to writing a good thesis project, what is writer’s block and how do you overcome it, how to write the perfect thesis statement for your master’s – 6 easy steps.

Senior Thesis

A senior thesis is more than a big project write-up. It is documentation of an attempt to contribute to the general understanding of some problem of computer science, together with exposition that sets the work in the context of what has come before and what might follow. In computer science, some theses involve building systems, some involve experiments and measurements, some are theoretical, some involve human subjects, and some do more than one of these things. Computer science is unusual among scientific disciplines in that current faculty research has many loose ends appropriate for undergraduate research.

Senior thesis projects generally emerge from collaboration with faculty. Students looking for senior thesis projects should tell professors they know, especially professors whose courses they are taking or have taken, that they are looking for things to work on. See the page on CS Research for Undergrads . Ideas often emerge from recent papers discussed in advanced courses. The terms in which some published research was undertaken might be generalized, relaxed, restricted, or applied in a different domain to see if changed assumptions result in a changed solution. Once a project gets going, it often seems to assume a life of its own.

To write a thesis, students may enroll in Computer Science 91r one or both terms during their senior year, under the supervision of their research advisor. Rising seniors may wish to begin thinking about theses over the previous summer, and therefore may want to begin their conversations with faculty during their junior spring—or even try to stay in Cambridge to do summer research.

An information session for those interested in writing a senior thesis is held towards the end of each spring semester. Details about the session will be posted to the  [email protected] email list.

Students interested in commercializing ideas in their theses may wish to consult Executive Dean Fawwaz Habbal about patent protection. See  Harvard’s policy  for information about ownership of software written as part of your academic work.

Thesis Supervisor

You need a thesis supervisor. Normally this is a Harvard Computer Science faculty member. Joint concentrators (and, in some cases, non-joint concentrators) might have a FAS/SEAS Faculty member from a different field as their thesis supervisor. Exceptions to the requirement that the thesis supervisor is a CS or FAS/SEAS faculty member must be approved by the Director of Undergraduate Studies. For students whose advisor is not a Harvard CS faculty member, note that at least one of your thesis readers must be a Harvard CS faculty member, and we encourage you to talk with this faculty member regularly to help ensure that your thesis is appropriately relevant for Harvard Computer Science.

It’s up to you and your supervisor how frequently you meet and how engaged the supervisor is in your thesis research. However, we encourage you to meet with your supervisor at least several times during the Fall and Spring, and to agree on deadlines for initial results, chapter outlines, drafts, etc.

Thesis Readers

The thesis is evaluated by the thesis readers. Thesis readers must be either:

Two Harvard CS faculty members/affiliates ; or:

Three readers, at least one of whom is a Harvard CS faculty member and the others are ordinarily teaching faculty members of the Faculty of Arts and Sciences or SEAS who are generally familiar with the research area.

The thesis supervisor is one of the readers.

The student is responsible for finding the other readers, but you can talk with your supervisor for suggestions of possible readers.

Exceptions to these thesis reader requirements must be approved by the Directors of Undergraduate Studies.

For joint concentrators, the other concentration may have different procedures for thesis readers; if you have any questions or concerns about thesis readers, please contact the Directors of Undergraduate Studies.

Senior Thesis Seminar

Computer Science does not have a Senior Thesis seminar course.

However, we do run an informal optional series of Senior Thesis meetings in the Fall to help with the thesis writing process, focused on topics such as technical writing tips, work-shopping your senior thesis story, structure of your thesis, and more. Pay attention to your email in the Fall for announcements about this series of meetings.

The thesis should contain an informative abstract separate from the body of the thesis. This abstract should clearly state what the contribution of the thesis is–which parts are expository, whether there are novel results, etc. We also recommend the thesis contain an introduction that is at most 5 pages in length that contains an “Our contributions” section which explains exactly what the thesis contributed, and which sections in the thesis these are elaborated on. At the degree meeting, the Committee on Undergraduate Studies in Computer Science will review the thesis abstract, the reports from the three readers and the student’s academic record; it will have access to the thesis.  The readers (and student) are told to assume that the Committee consists of technical professionals who are not necessarily conversant with the subject matter of the thesis so their reports (and abstract) should reflect this audience.

The length of the thesis should be as long as it needs to be to present its arguments, but no longer!

There are no specific formatting guidelines. For LaTeX, some students have used this template in the past . It is set up to meet the Harvard PhD Dissertation requirements, so it is meeting requirements that you as CS Senior Thesis writers don’t have.

Thesis Timeline for Seniors

(The timeline below is for students graduating in May. For off-cycle students, the same timeline applies, but offset by one semester. The thesis due date for March 2025 graduates is Friday November 22, 2024 at 2pm. The thesis deadline for May 2024 graduates is Friday March 29th Monday April 1st at 2pm.

Please be aware that students writing a joint thesis must meet the requirements of both departments–so if there are two different due dates for the thesis, you are expected to meet the earlier date.

Senior Fall (or earlier) Find a thesis supervisor, and start research. 

October/November/December Start writing.

All fourth year concentrators are contacted by the Office of Academic Programs and those planning to submit a senior thesis are requested to supply certain information, including name of advisor and a tentative thesis title. You may use a different title when you submit your thesis; you do not need to tell us your updated title before then. If Fall 2024 is your final term, please fill out this form . If May 2024 is your final term, please fill out this form .

Early February The student should provide the name and contact information for the readers (see above), together with assurance that they have agreed to serve. 

Mid-March Thesis supervisors are advised to demand a first draft. (A common reaction of thesis readers is “This would have been an excellent first draft. Too bad it is the final thesis—it could have been so much better if I had been able to make some suggestions a couple of weeks ago.")

April 1, 2024 * Thesis is due by 2:00 pm. Electronic copies in PDF format should be delivered by the student to all three readers and to [email protected] (which will forward to the Director of Undergraduate Studies) on or before that date. An electronic copy should also be submitted via the SEAS online submission tool on or before that date. SEAS will keep this electronic copy as a non-circulating backup. During this online submission process, the student will also have the option to make the electronic copy publicly available via DASH, Harvard’s open-access repository for scholarly work. Please note that the thesis will NOT be published to ProQuest. More information can be found on the SEAS  Senior Thesis Submission  page.

The two or three readers will receive a rating sheet to be returned to the Office of Academic Programs before the beginning of the Reading Period, together with their copy of the thesis and any remarks to be transmitted to the student.

Late May The Office of Academic Programs will send students their comments after the degree meeting to decide honors recommendations.

Thesis Extensions and Late Submissions

Thesis extensions Thesis extensions will be granted in extraordinary circumstances, such as hospitalization or grave family emergency, with the support of the thesis advisor and resident dean and the agreement of all readers. For joint concentrators, the other concentration should also support the extension. To request an extension, please have your advisor or resident dean email [email protected] , ideally several business days in advance, so that we may follow up with readers. Please note that any extension must be able to fall within our normal grading, feedback, and degree recommendation deadline, so extensions of more than a few days are usually impossible.

Late submissions Late submission of thesis work should be avoided. Work that is late will ordinarily not be eligible for thesis prizes like the Hoopes Prize. Theses submitted late will ordinarily be penalized one full level of honors (highest honors, high honors, honors, no honors) per day late or part thereof, including weekends, so a thesis submitted two days and one minute late is ordinarily ineligible to receive honors. Penalties will be waived only in extraordinary cases, such as documented medical illness or grave family emergency; students should consult with the Directors of Undergraduate Studies in that event. Missed alarm clocks, crashed computers, slow printers, corrupted files, and paper jams are not considered valid causes for extensions.

Thesis Examples

Recent thesis examples can be found on the Harvard DASH (Digital Access to Scholarship at Harvard) repository here . Examples of Mind, Brain, Behavior theses are here .

Spectral Sparsification: The Barrier Method and its Applications

• Martin Camacho, Advisor: Jelani Nelson

Good Advice Costs Nothing and it’s Worth the Price: Incentive Compatible Recommendation Mechanisms for Exploring Unknown Options

• Perry Green, Advisor: Yiling Chen

Better than PageRank: Hitting Time as a Reputation Mechanism

• Brandon Liu, Advisor: David Parkes

Tree adjoining grammar at the interfaces

• Nicholas Longenbaugh, Advisor: Stuart Shieber

SCHUBOT: Machine Learning Tools for the Automated Analysis of Schubert’s Lieder

• Dylan Nagler, Advisor: Ryan Adams

Learning over Molecules: Representations and Kernels

• Jimmy Sun, Advisor: Ryan Adams

Towards the Quantum Machine: Using Scalable Machine Learning Methods to Predict Photovoltaic Efficacy of Organic Molecules

• Michael Tingley, Advisor: Ryan Adams

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101 Best Computer Science Topics for 2023

Any student will know the difficulty that comes with developing and choosing a great topic in computer science. Generally speaking, a good topic should be original, interesting, and challenging. It should push the limits of the field of study while still adequately answering the main questions brought on by the study.

We understand the stress that this may cause students, which is why we’ve dedicated our time to search the web and print resources to find the latest computer science topics that create the biggest waves in the field. Here’s the list of the top computer science research topics for 2023 you can use for an essay or senior thesis :

AP Computer Science Topics for Students Entering College

• How has big data impacted the way small businesses conduct market research?
• Does machine learning negatively impact the way neurons in the brain work?
• Did biotech change how medicine is administered to patients?
• How is human perception affected by virtual reality technologies?
• How can education benefit from using virtual reality in learning?
• Are quantum computers the way of the future or are they just a fad?
• Has the Covid-19 pandemic delayed advancements in computer science?

Computer Science Research Paper Topics for High School

• How successful has distance learning computer tech been in the time of Covid-19?
• Will computer assistance in businesses get rid of customer service needs?
• How has encryption and decryption technology changed in the last 20 years?
• Can AI impact computer management and make it automated?
• Why do programmers avoid making a universal programming language?
• How important are human interactions with computer development?
• How will computers change in the next five to ten years?

Controversial Topics in Computer Science for Grad Students

• What is the difference between math modeling and art?
• How are big-budget Hollywood films being affected by CGI technologies?
• Should students be allowed to use technology in classrooms other than comp science?
• How important is it to limit the amount of time we spend using social media?
• Are quantum computers for personal or home use realistic?
• How are embedded systems changing the business world?
• In what ways can human-computer interactions be improved?

Computer Science Capstone Project Ideas for College Courses

• What are the physical limitations of communication and computation?
• Is SCRUM methodology still viable for software development?
• Are ATMs still secure machines to access money or are they a threat?
• What are the best reasons for using open source software?
• The future of distributed systems and its use in networks?
• Has the increased use of social media positively or negatively affected our relationships?
• How is machine learning impacted by artificial intelligence?

Interesting Computer Science Topics for College Students

• How has Blockchain impacted large businesses?
• Should people utilize internal chips to track their pets?
• How much attention should we pay to the content we read on the web?
• How can computers help with human genes sequencing?
• What can be done to enhance IT security in financial institutions?
• What does the digitization of medical fields mean for patients’ privacy?
• How efficient are data back-up methods in business?

Hot Topics in Computer Science for High School Students

• Is distance learning the new norm for earning postgraduate degrees?
• In reaction to the Covid-19 pandemic should more students take online classes?
• How can game theory aid in the analysis of algorithms?
• How can technology impact future government elections?
• Why are there fewer females in the computer science field?
• Should the world’s biggest operating systems share information?
• Is it safe to make financial transactions online?

Ph.D. Research Topics in Computer Science for Grad Students

• How can computer technology help professional athletes improve performance?
• How have Next Gen Stats changed the way coaches game plan?
• How has computer technology impacted medical technology?
• What impact has MatLab software had in the medical engineering field?
• How does self-adaptable application impact online learning?
• What does the future hold for information technology?
• Should we be worried about addiction to computer technology?

Computer Science Research Topics for Undergraduates

• How has online sports gambling changed IT needs in households?
• In what ways have computers changed learning environments?
• How has learning improved with interactive multimedia and similar technologies?
• What are the psychological perspectives on IT advancements?
• What is the balance between high engagement and addiction to video games?
• How has the video gaming industry changed over the decades?
• Has social media helped or damaged our communication habits?

Research Paper Topics in Computer Science

• What is the most important methodology in project planning?
• How has technology improved people’s chances of winning in sports betting?
• How has artificial technology impacted the U.S. economy?
• What are the most effective project management processes in IT?
• How can IT security systems help the practice of fraud score generation?
• Has technology had an impact on religion?
• How important is it to keep your social networking profiles up to date?

More Computer Science Research Papers Topics

• There is no area of human society that is not impacted by AI?
• How adaptive learning helps today’s professional world?
• Does a computer program code from a decade ago still work?
• How has medical image analysis changed because of IT?
• What are the ethical concerns that come with data mining?
• Should colleges and universities have the right to block certain websites?
• What are the major components of math computing?

Computer Science Thesis Topics for College Students

• How can logic and sets be used in computing?
• How has online gambling impacted in-person gambling?
• How did the 5-G network generation change communication?
• What are the biggest challenges to IT due to Covid-19?
• Do you agree that assembly language is a new way to determine data-mine health?
• How can computer technology help track down criminals?
• Is facial recognition software a violation of privacy rights?

Quick and Easy Computer Science Project Topics

• Why do boys and girls learn the technology so differently?
• How effective are computer training classes that target young girls?
• How does technology affect how medicines are administered?
• Will further advancements in technology put people out of work?
• How has computer science changed the way teachers educate?
• Which are the most effective ways of fighting identify theft?

Excellent Computer Science Thesis Topic Ideas

• What are the foreseeable business needs computers will fix?
• What are the pros and cons of having smart home technology?
• How does computer modernization at the office affect productivity?
• How has computer technology led to more job outsourcing?
• Do self-service customer centers sufficiently provide solutions?
• How can a small business compete without updated computer products?

Computer Science Presentation Topics

• What does the future hold for virtual reality?
• What are the latest innovations in computer science?
• What are the pros and cons of automating everyday life?
• Are hackers a real threat to our privacy or just to businesses?
• What are the five most effective ways of storing personal data?
• What are the most important fundamentals of software engineering?

Even More Topics in Computer Science

• In what ways do computers function differently from human brains?
• Can world problems be solved through advancements in video game technology?
• How has computing helped with the mapping of the human genome?
• What are the pros and cons of developing self-operating vehicles?
• How has computer science helped developed genetically modified foods?
• How are computers used in the field of reproductive technologies?

Our team of academic experts works around the clock to bring you the best project topics for computer science student. We search hundreds of online articles, check discussion boards, and read through a countless number of reports to ensure our computer science topics are up-to-date and represent the latest issues in the field. If you need assistance developing research topics in computer science or need help editing or writing your assignment, we are available to lend a hand all year. Just send us a message “ help me write my thesis ” and we’ll put you in contact with an academic writer in the field.

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Title: fundamental components of deep learning: a category-theoretic approach.

Abstract: Deep learning, despite its remarkable achievements, is still a young field. Like the early stages of many scientific disciplines, it is marked by the discovery of new phenomena, ad-hoc design decisions, and the lack of a uniform and compositional mathematical foundation. From the intricacies of the implementation of backpropagation, through a growing zoo of neural network architectures, to the new and poorly understood phenomena such as double descent, scaling laws or in-context learning, there are few unifying principles in deep learning. This thesis develops a novel mathematical foundation for deep learning based on the language of category theory. We develop a new framework that is a) end-to-end, b) unform, and c) not merely descriptive, but prescriptive, meaning it is amenable to direct implementation in programming languages with sufficient features. We also systematise many existing approaches, placing many existing constructions and concepts from the literature under the same umbrella. In Part I we identify and model two main properties of deep learning systems parametricity and bidirectionality by we expand on the previously defined construction of actegories and Para to study the former, and define weighted optics to study the latter. Combining them yields parametric weighted optics, a categorical model of artificial neural networks, and more. Part II justifies the abstractions from Part I, applying them to model backpropagation, architectures, and supervised learning. We provide a lens-theoretic axiomatisation of differentiation, covering not just smooth spaces, but discrete settings of boolean circuits as well. We survey existing, and develop new categorical models of neural network architectures. We formalise the notion of optimisers and lastly, combine all the existing concepts together, providing a uniform and compositional framework for supervised learning.

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MIT Libraries home DSpace@MIT

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This collection of MIT Theses in DSpace contains selected theses and dissertations from all MIT departments. Please note that this is NOT a complete collection of MIT theses. To search all MIT theses, use MIT Libraries' catalog .

MIT's DSpace contains more than 58,000 theses completed at MIT dating as far back as the mid 1800's. Theses in this collection have been scanned by the MIT Libraries or submitted in electronic format by thesis authors. Since 2004 all new Masters and Ph.D. theses are scanned and added to this collection after degrees are awarded.

MIT Theses are openly available to all readers. Please share how this access affects or benefits you. Your story matters.

If you have questions about MIT theses in DSpace, [email protected] . See also Access & Availability Questions or About MIT Theses in DSpace .

If you are a recent MIT graduate, your thesis will be added to DSpace within 3-6 months after your graduation date. Please email [email protected] with any questions.

Permissions

MIT Theses may be protected by copyright. Please refer to the MIT Libraries Permissions Policy for permission information. Note that the copyright holder for most MIT theses is identified on the title page of the thesis.

Theses by Department

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• Engineering Systems Division
• Harvard-MIT Program of Health Sciences and Technology
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• Media Arts & Sciences
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• Technology and Policy Program

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Doctoral theses, graduate theses, undergraduate theses, recent submissions.

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DalSegno: User-centric preference elicitation strategies for mitigating cold start in music recommender systems 

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Master's Theses and Projects

The objective of the mandatory Master's Thesis or Project requirement is to provide a culminating educational experience, where the student, under the supervision of a faculty member, conducts an individual study employing concepts and methods learned in the program to solve a problem of significant importance from a practical or theoretical standpoint.

The Following Policies Apply

Study involves overview.

The study should involve a synthesis of concepts and methods learned in more than one course, and exhibit awareness of previous work in the area of study. This requirement also aims to provide an opportunity to the student to learn and practice the means of written and oral communication. The project or thesis provides an extremely important component to the students' portfolio applied towards a future undertaking whether it be for admission to a Ph.D. program or for a leadership position in the computing industry.

Two Equivalent Possibilities

There are two equivalent possibilities for the culminating experience in the MS program in Computer Science: MS project (CSC 895) , and MS thesis (CSC 898) . The MS thesis and the MS project have the same level of difficulty, need the same time for completion, and yield the same kind of MS degree. The decision whether a work is a thesis or a project must be made at the time of registration for CSC 895/898 in consultation with the faculty advisor.

1. Credits and Courses to Take

The complete work on MS thesis/project has a limit of 9 credits. Typically, students working on a thesis will register for 3 credits of CSC 897 (Research) followed by 3 credits of CSC 898, but they can take an additional 3 units of CSC 897 upon advisement. Students working on a project will usually enroll in 3 credits of CSC 899 followed by 3 credits of CSC 895,but they can take additional 3 units of CSC 899 upon advisement. CSC 895 and 898 are graded as CR/NC.

2. Advisor and Committee Selection

Before registering for the MS thesis/project the student must select an advisor, and other members of the thesis/project committee and file the GAP and Culminating Experience Form with the Graduate Division. The thesis committee must have at least 3 members, and the project committee must have at least 2 members. At least two members must be tenured or tenure-track SFSU/CS faculty for either type of committee. In addition to the 2 members of the CS Department, the committee may include faculty or members outside of the CS Department, upon approval of the CS Chair.

Both MS thesis and MS project have a public oral defense. Usually the student presentation is about 30 min. with Q&A following. Defense committee then asks all to leave the room for a short period of time to discuss the work and the grading. The defense must be advertised to the local community. This is a great opportunity to bring family and friends. Students are advised to carefully rehearse and check the presentation for content, duration and to make sure all the SW and demos work.

4. MS Thesis Format

The format of the MS thesis document is strictly defined and controlled by the SF State Graduate Division ( University Thesis Composition Guidelines ). The original copy of the thesis, including committee signatures, is submitted to the Graduate Division for approval. After approval by the Graduate Division the original version is bound according to the SFSU standard and available in the SFSU library. One bound copy of the thesis must also be given to the CS Department office. Thesis copies are submitted to the committee members in a form approved by the members.

5. MS Project Format

The format of the MS project document is strictly defined and controlled by the Department of Computer Science, and has the form of the CS Technical Report. The final version of the MS project is submitted to the CS Department and stored in the CS Department office. Project document copies are submitted to the committee members in a form approved by the members. Please work with your advisor for more details.

6. Deadlines, Forms & Paperwork

Students are encouraged to consult with prospective thesis/project advisors and CS office for more detailed information on the expected schedules for completion of their culminating experience work.

Note: CSC 895 enrollment (permit number) is strictly controlled by CS Office and not your mentor. This is due to the need to make a complete check on whether you fulfilled all the requirements for graduation.

The deadline for filing all forms for your CSC 895/898 is the semester preceding your planned CSC 895/898 enrollment (November for Spring and April for Fall). See your grad advisor and CS office for details, and check the above link.

7. Culminating Experience Project Proposal

This is submitted the term prior to enrollment in 895 or 898. The CER is a vehicle to communicate and agree upon expectations for the work for culminating experience between the student and the advisor. Typical sections of this proposal should include motivation, problem description, method of solving the problem, relevant work of others, as well as milestones, deliverables and approximate timetable (for more details talk with the thesis/project advisor). This project proposal should be done carefully and will serve as a "contract" between the advisor and the student. The size of this report is in general about 2-4 pages. Students are encouraged to work with their thesis/project advisor on specific details.

It is required that this proposal be developed as a deliverable with the 899 or 897 course preceding 895 or 898 courses.

8. Student Responsibility

It is  critical  to plan to take graduate level electives with possible culminating experience supervisors during your first year of study. Think of topic(s) for your culminating experience, do a research on it, check what CS faculty does for research, and feel free to meet CS Chair or other faculty for advice.

• Must  attend the first graduate seminar (graduate program overview) in your first semester of study
• Must  enroll in courses taught by prospective thesis/project supervisors in your second semester of study. Consult your favorite professors for guidance in project selection.
• Must  attend mandatory advising group meeting with CS Chair to be organized within the first 4 weeks of second semester.
• Must  select your culminating experience supervisor by the end of second semester and obtain your supervisor's permission to work under his/her supervision.

The culminating project and thesis require serious commitment and focus of the student. Serve the purpose to show that the student is capable of delivering individual work as well as being independent, able to deliver a project etc.

It is the responsibility of the student to follow up the agreed upon milestones and commitments made to the advisors (typically via approved project proposal). This is especially critical for projects where the work involves external funding and commitments including developing publications that require student's contributions.

Students are strongly encouraged to help faculty develop research publications (e.g. doing the necessary work such as SW development, experiments) and to participate in writing research papers, especially those aspiring toward Ph. D. studies.

While students own the copyright to the code they develop at SF State, the source code, and all the data and procedures used for the research and experiments, must be made publicly available for faculty and others for the purpose of grading and evaluation.

Changes in project plans, topics, title or committee members (but not the main advisor) must be made in writing in accordance with Department procedures. Change of advisor requires repeating the whole culminating project or thesis course sequence (including 899 or 897) and adherence to Department polices.

Students must follow all CS Department and general rules about plagiarism. Details are available at  Department Cheating and Plagiarism Policy Web Page

Other Options to Finish Culminating Experience

If you do not finish your culminating experience within two semester, you must enroll in culminating experience through CEL. More about enrolling through CEL. 

CS Department Information

Information and deadlines.

Advancement to Candidacy (ATC)

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Proposal for Culminating Experience Form (CEF)

• University Culminating Experience Procedures

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Graduate Seminars (PERNET)

• Complete the semester PRIOR to 895/898 enrollment
• Department Graduate Seminar Series

895/898 Enrollment

• Need ALL of the above submitted/completed the semester PRIOR to enrollment in 895/898
• Department Checklist for Enrolling in 895/898 PDF

Thesis Defense (Complete Culminating Experience)

• University Graduate Students Deadlines
• Department Oral and Written Defense

Oral and Written Defense

If you are a Graduate Student, in your last semester and planning to graduate, you need to write up your project report or thesis, and prepare for your Oral Defense. Please follow the steps and timeline below for writing up your project report/thesis and oral defense. We urge you to work closely with your project/thesis advisor, to clarify expectations, confirm deadlines, and coordinate other committee members.

Steps for Completing Your Culminating Experience Project/Master's Thesis

• The last day to submit your "Report of Completion" is the last day of instruction (not the last day of final exams). Your committee members need ample time to read and review your written report. Plan accordingly. All programming should be done, most experiments completed and you should have a solid first draft report written by the second week of the semester. Submit the masters project/thesis write up to your project/thesis advisor for content approval no later than the 6th week of the semester. This allows you time to correct for proper grammar as well as make any other edits based on your advisor's feedback. Students completing the thesis option are referred to the University Gradute Studies website  for guidelines on formatting the thesis report, as well as instructions on submitting final copies.
• Once the project/thesis advisor approves the report/thesis, the student submits copies to all committee members for their approval of the CONTENT.
• Student confers with faculty to determine the date and time all committee members are available for the Oral Defense
• Student submits abstract and keywords to project/thesis advisor for approval
• The student works with the committee to resolve any issues with the report submitted in Steps 1. and 2. above. After all issues with the written report are resolved, the student is given the (official) signed signature sheets and cover sheet to include with the written report
• Students submitting a thesis write-up are referred to the  Graduate Division website  for instruction on submitting final copies.
• Students submitting a project write-up should use the plastic (white) binding combs, thick black plastic sheet on the back and thick clear plastic sheet on the front. The number of copies depends upon the committee - minimal of 2 copies. The original version is provided to the office.
• In preparing for oral presentation, students must review instructions and guidelines for  Department Preparing Oral Presentation web page  and confirm this to their advisor.
• Department Writing Culminating Experience Reports (CER) Web Page

Writing a Culminating Experience Report (CER)

In this section we will outline what constitutes an outstanding culminating experience report (CER) whether it is Thesis or a Project; what constitutes unacceptable one; and also outline our general recommendations for the CER outline and content of each chapter.

The focus here is on the write-up part of the CER, namely how to communicate it in the written form (i.e. CER), and not on the culminating experience project itself. Please note that the final decision and guidance on this comes from your Culminating Experience Committee Chair and committee members, but we believe that the material in this section is general enough to set you on the right path. Finally, we will reiterate some recommendations on your oral presentation of CER.

More details on what kinds of CER exist (Thesis or Project) are located at:  Department M.S. Culminating Experience Requirments .

Steps in completing the Culminating Experience are located at:  Department Writen and Oral Defense Information .

To help you improve your writing skills, all of our students are encouraged to take an online writing course such as the one offered through courses at Stanford University, titled "Writing in the Sciences" offered during the Fall semester. For more information:  Stanford Writing in the Sciences Course Information .

Very good resources on how to write technical reports are here:

• Colubia Web Page: Writing Technical Articles .
• Columbia Web Page: Common Bugs in Writing .

Before we start, let us reiterate that completing culminating experience (both the project and the report) is primarily the responsibility of the student and hence the student has to drive it. It is not expected from the faculty to fully participate in writing the CER or in very extensive editing except to give necessary feedback and comments. We strongly recommend that high level CER outline be agreed between student and faculty before the writing commences.

Let us first see what constitutes an outstanding CER and what constitutes an unacceptable CER. While the definitions below touch upon the project work itself, please focus for now on the suggestions that refer to the ways on how to write about it.

Preparing Oral Presentations

Being able to present your work is critically important for your future career as well as for the oral defense of your culminating project or thesis. Please consult the following resources in preparing for your oral defense. Be sure to test your presentation on the exact same computer and projector which you will use during your presentation.

Performance Juxtaposition Web Page: Presentations

Student Theses and Projects

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Thesis Guide

Advice for great computer science thesis projects.

My thesis project was the most rewarding experience of my computer science studies. Unfortunately, many students suffer theirs as frustrating, tedious and with few opportunities for personal growth.

In this guide, I want to share the pitfalls and best practices from supervising 50+ thesis projects in computer science at TUM . I hope that it helps you write a great thesis and grow in the process.  Start reading here .

Slides From My Presentations

We provide slides in English from January 2024 . The slides on how to write a guided research are from Roman’s talk from January 2024.

For more information on how to write a thesis at the company Elmar has founded, we recommend our software intelligence night. Please register such that we can order enough pizza and beer for everyone!

Video Recordings

Below are videos that summarize the thesis guide content. The first one is in German, the second one in in English.

German version:

English version:

Recent Posts

Talk at tum: how to write a great master’s thesis, talk at tum: how to do a guided research, avoiding typical pitfalls (not only) at tum, from thesis to paper: my first publication on a scientific conference, how to write a case study.

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How to search for Harvard dissertations

• DASH , Digital Access to Scholarship at Harvard, is the university's central, open-access repository for the scholarly output of faculty and the broader research community at Harvard.  Most Ph.D. dissertations submitted from  March 2012 forward  are available online in DASH.
• Check HOLLIS, the Library Catalog, and refine your results by using the   Advanced Search   and limiting Resource  Type   to Dissertations
• Search the database  ProQuest Dissertations & Theses Global Don't hesitate to  Ask a Librarian  for assistance.

How to search for Non-Harvard dissertations

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• Many  universities  provide full-text access to their dissertations via a digital repository.  If you know the title of a particular dissertation or thesis, try doing a Google search.  

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Computer Science: Theses and dissertations

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• ORA: Oxford University Research Archive by Jason Partridge Last Updated Jan 9, 2024 1172 views this year

Tips for Finding Theses at Oxford

SOLO now allows you to search for theses in the Oxford collections very easily.

1. Navigate to the SOLO homepage.

2. Type details of the Thesis you would like to search for into the main search box.

3. Under the search box is a series of drop-down menus marked 'Refine your search'. In the first box select the the ' Theses ' option.

4. Now press the ' Search ' button to run your search.

Oxford Theses

• SOLO Search for print and electronic Oxford DPhil theses in the library catalogue. Electronic versions will link directly to the record in ORA. Limit your search to "Theses".
• Oxford Research Archive (ORA) Search for and download recent (2006+) Oxford DPhil theses.

Non-Oxford Theses

• EThOS Access to UK theses from the British Library. [*Note: You will need to register to access theses through EThOS.] more... less... To use this service you will be required to set up an individual account.
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• Proquest Dissertations and Theses Search US theses and dissertations. Accessed through OxLip+, search for 'dissertations and theses'.
• NDLTD Networked Digital Library of Theses and Dissertations. Search and access e-theses and dissertations from around the world.

The  Oxford University Research Archive (ORA)  contains research publications and other research output produced by members of the University of Oxford. Content includes copies of journal articles, conference papers and theses.

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Thesis/Project Student Process

The following process applies to all Division of Computing & Software Systems (CSS) graduate students, regardless of degree program (CSSE or CSE) or thesis/project goals.

In general, a thesis is a scholarly written document aimed at an academic audience as a contribution to an existing body of knowledge. A project is aimed at building a connection between academic concepts and the application of those concepts into real-world context.

Before students determine which option to pursue, they should discuss how each option applies to their own individual goals for their degree program with their faculty advisor and the CSS Graduate Advisor.

Step 1: Form a Supervisory Committee

Students who desire to register for their thesis/project credit(s) must first form a committee of faculty who will supervise and grade their efforts and results of their work. A supervisory committee will consist of a student’s Faculty Advisor (who will serve as Committee Chair) and at least 2-3 additional faculty members. At least two of the committee members must be faculty whose primary appointment is in the Computing & Software Systems Division. The Chair of the Committee and at least one-half of the total membership must be members of the graduate faculty.

Students must submit a signed Request to Form a Supervisory Committee to the CSS Graduate Advisor to obtain an entry code to register for the class. Included with the signed form should be a proposal (minimally 3 pages) addressing the questions asked in section 2 of the form. Please follow the proposal guidelines detailed in the link below:

• Proposal Guidelines
• Proposal Rubric

Before submitting the form, students are expected to attend another students CSS master’s project or thesis final examination & defense. View the Thesis/Project Final Exam Schedule .

The deadline for all committee requests is the first day of the seventh week of the quarter PRECEDING the start of a student’s project or thesis coursework . Students should request for specific faculty to staff their Supervisory Committee; however, final staffing assignments of the Supervisory Committee resides with the CSS Division’s Graduate Program Coordinator. Once a supervisory request has been granted, students will receive an email from the CSS Graduate Advisor notifying them of the approved committee and an entry code to register for their thesis/project credit(s). Students are encouraged to submit their request early, to avoid any registration late fees.

Submission Deadlines

• Winter 2024: November 6, 2023
• Spring 2024: February 12, 2024
• Summer 2024: May 6, 2024
• Autumn 2024: July 29, 2024

Step 2: File a Thesis or Project Plan

By the end of the second week of the quarter in which a student is registered for their first capstone credits, the student must submit to their Supervisory Committee a detailed project or thesis plan. The plan should include an updated proposal of the work to be done, a time table listing key milestones and associated deliverables, the quality criteria and specific metrics by which student expects to measure the quality of their result, and the software development lifecycle and processes planned to complete the work. There are no penalties for deviations in the approved plan or failure to meet the estimates in the timetable or failure to achieve the quality goals. The plan simply provides a well-defined start for the remainder of the capstone work. A PDF copy of the approved plan must be submitted by the student to the STEM Graduate Advising Office.

• Winter 2024: January 16, 2024
• Spring 2024: April 8, 2024
• Summer 2024: July 1, 2024

To submit your plan to the STEM Graduate Office, please send your PDF document to [email protected] , with the subject line “Project Plan” or “Thesis Plan”.

Register for CSSSKL 594

A substantial working draft of the capstone research project paper or thesis should be completed by the beginning of the quarter in which you expect to graduate. For this reason, generally, you will enroll in CSSSKL 594 “Scientific Writing for Thesis/Project” during the quarter before you expect to graduate. (For example, to graduate in the spring, you should enroll in 594 in the Winter). Please consult with your supervisory committee chair as to the best timing of this class for the most benefit to you.

Step 3: Communicate Regular Progress Reports with the Supervisory Committee

Throughout the period of enrollment in the thesis/project credit(s), students are expected to lead the effort to regularly update their Supervisory Committee members on their work progress. Students should plan on meeting with their Committee Chair frequently based on the advice from the committee chair (minimally three times in each quarter that they are enrolled for thesis/project credits).

To register for second and subsequent quarters, students should work with their Chair to determine the workload for the upcoming quarter and the number of credits to enroll for. Once the Committee Chair grants permission and confirms the number of credits for the next quarter, the student forwards that permission to the CSS Graduate Advisor, who will issue a new entry code to use for registration. In cases where satisfactory progress is made, the student will be issued of a grade of N (in progress) until the project/thesis is complete.

Students who fail to make appropriate progress in their project/thesis during a quarter may receive a notification from their Chair warning them of lack of progress. If students continue failing to achieve satisfactory progress, Chairs may also choose to issue a grade of NC (No Credit) and move to dissolve the Committee. For full information regarding the project/thesis continuation policy, please see the Academic Progress Policy .

• Guidelines for Status Reports
• Rubric for Status Reports

Step 4: Schedule Final Defense

By 5PM on Thursday of the third week of the quarter that a student is registered for their final thesis/project credits, the student must consult with their supervisory committee members to schedule a defense of their culminating work. Students should work closely with their committee chair to ensure that they are ready for their final examination and defense. The STEM Graduate Advising Office will send students the link to the online scheduling system each quarter to select a time/date for their defense. View details about defense format options and attendance requirements in the Defense Attendance Policy .

Step 5: Apply to Graduate

By 5:00 p.m. on Thursday of the third week of the quarter that a student is registered for their final degree credits the student must apply to graduate by filing a master’s degree request online . Students should work with the CSS Graduate Advisor and Committee Chair to plan their degree curriculum accordingly, so that their final capstone requirements serve as the culmination of their degree coursework. Students must be registered for credits during the quarter they want to graduate.

Step 6: Submit Draft of Final Paper/Thesis

Writing the final paper/thesis is a time intensive process. Students should plan ahead to schedule substantial time to compose and proofread their paper/thesis. A low-quality paper/thesis may lead to the delay of their defense. Early in the quarter that a student is registered for their final thesis/project credits, the student must review the following sample templates and discuss with their committee chair on the preference for the organization of their final project or thesis report:

• Guidelines from the UW Graduate School for thesis document
• Word template for thesis and project papers
• Latex template for thesis and project papers

Two weeks before the defense , submit the title and abstract to the School of STEM Office of Graduate Studies to post on the Final Examination & Defense schedule.

At least seven days before the defense, the student must submit a final draft of their project paper or thesis to their committee for a preliminary reading. The purpose of this draft is to demonstrate to the Supervisory Committee that the student has achieved a Master’s level competency in computer science and software engineering, and that the student is ready to defend their work.

Step 7: Final Examination and Defense

The Final Examination and Defense consists of (a) a public student presentation, (b) a public questions and answers session, (c) a closed-door question and answer session between the student and the Supervisory Committee, (d) a brief private discussion among the Supervisory Committee, and (e) the Supervisory Committee announcing to the student the result of the Final Examination and Defense. A typical defense will last close to two hours. If a student does not pass the Final Examination and Defense, the Supervisory Committee will work with the student to decide upon the necessary additional work required for obtaining their Master’s degree. The final examination and defense must take place no later than the third day of the last week of the quarter (final exam week).

• Presentation Guidelines
• Presentation Rubric

Step 8: File your Thesis or Project Paper

After passing their final examination/defense, students must submit an electronic copy (PDF) of their final project paper or thesis, incorporating any post examination/defense revisions required by their Committee to the following entities in the order listed:

• Supervisory Committee members, by the time/date given to students by their Chairs. This deadline will vary, based on the date of the student’s defense and scope of requested changes. Students must receive approval of final document from their Committee before submitting the paper to the STEM Graduate Office (all students) and the UW Graduate School (thesis students only).
• STEM Graduate Office by 11:59 p.m. on the final day of the quarter in which the student intends to graduate. See submission instructions below.
• Thesis Students only: UW Graduate School by 11:59 p.m. on the last day of the quarter in which the student intends to graduate. This step applies to thesis students only. See “Special Notes for Thesis Students” section below.

Failure to complete any of the above steps by the appropriate time/date will result in a delay of graduation.

Students submit their final document to the STEM Graduate Office ( [email protected] ) with their supervisory committee members copied on the email, and the email subject as “Final Thesis”, or “Final Project Report.”

Special Notes for Thesis Students

• Formatting and process : Thesis students must meet formatting requirements, and follow a specific submission process. Students are urged to read the UW thesis formatting guidelines well in advance of their final examination, and to set up their ProQuest account early in the quarter they intend to graduate.
• Master’s Supervisory Committee Form : Thesis students must submit a signed Master’s Supervisory Committee Form as part of the ETD submission process.

Additional Information

• Summary of Master’s Guidelines & Rubrics Documents
• Video Overview and Guideline

• WFU HOMEPAGE
• WFU DIRECTORY

WAKE FOREST UNIVERSITY DEPT OF COMPUTER SCIENCE GRADUATE PROGRAM

Thesis & Projects

ADOPTED JANUARY 5, 2005

Thesis Policy Statement

The thesis option in Computer Science permits students to carry out a research program that is then embodied in the thesis document. As stipulated by the graduate school, the thesis must be presented to a faculty committee that examines the student’s knowledge in the area of the thesis and related areas. Ideally, this research will produce a publication for the student. The Dean of the Graduate School appoints the members of the examining committee which makes a recommendation to the Dean of the Graduate School as to whether the thesis should or should not be approved.

The Graduate School states in the Instructions for the Preparation of Theses and Dissertations: “The path of their research will take them to new knowledge, new insights, new abstractions for themselves, and as they push toward and beyond the current boundaries of what is known, they will be expected to share their new knowledge with others. This sharing is the primary purpose of a thesis or dissertation. It provides an opportunity for students to be challenged intellectually in an oral defense of their work, to have their ideas tested in a scholarly setting, and to enter the world of advanced scholarly attainment.”

ADOPTED NOVEMBER 19, 2015

Thesis Proposal Requirement

Students completing the thesis option should prepare and present a thesis proposal document as outlined in the following text.

By the last day of classes of the student’s second semester of the program, the student should submit to the graduate program director the name of the faculty adviser with whom the student plans to work and a 1-paragraph description of the broad topic of the proposed thesis work.

Within 30 days from the start of classes of the third semester of the program (or the semester before anticipated graduation if on a timeline that requires less than four semesters), the student should finalize thesis committee members consisting of three faculty members, of which at least two are Computer Science Department faculty and should submit a 6 to 8 page thesis proposal document to the thesis committee   This document should be formatted using the Wake Forest University thesis template guidelines and include: Problem statement, including the importance of the problem; Discussion and critique of prior work in the area; Overview of the proposed approach; and Expected outcomes of the research.

The student should schedule a committee meeting to be held within the 30 days in which the committee reviews the student’s plans and provides feedback and approval of the proposed work. The presentation should be scheduled to last between 20 and 30 minutes and focus on addressing the four components of the proposal document.   The presentation will be open to the committee and other interested faculty but not the public and the proposal document should be submitted to the committee at least one week before the scheduled presentation.

COMPUTER SCIENCE

Masters Thesis Template

The Graduate School requires a strict format for masters theses and doctoral dissertations, as these are archival documents stored in the department and at the University. A link to the textual description of the requirements for thesis formatting can be found at the Graduate School Website .

If you decide to use Latex to typeset your thesis, a Latex class file that provides formatting that fits the Wake Forest University standards is available. The file can be accessed below.

The first chapter of your thesis must be checked for formatting approximately a month before the end of the semester in which you intend to graduate and submit your document. The exact deadlines for this format check can be found on the Graduate School Calendar .

Project Policy Statement

The project option in computer science affords a student a software design and program development experience. Often this will be in conjunction with faculty research. The project option consists of both a complete software design using accepted software engineering methodology and a successful software implementation under the supervision of a project adviser. Final approval of the project is given by the student’s Project Committee.

A student must find a faculty adviser with whom to work on the project. Typically the project will have a natural relationship with the adviser’s research. More than one student may work with an adviser on a related topic, but each must satisfy the requirements of the project completely.

Each student’s Project Committee will be composed of at least three members of the Computer Science Department: a project adviser, an individual to serve as the Project Committee chair, and one more department member. At least two of the three members of the Project Committee must be members of the Graduate Faculty of the University. The Project Committee will decide upon the acceptability of both the proposed project and the final design document and implementation resulting from the approved design proposal.

All projects must explicitly comply with some widely accepted software engineering methodology.

For example, the seven critical steps as specified in the Waterfall Methodology found in standard software engineering texts: feasibility, requirements, design and analysis, code and module testing, integration and system testing, delivery and deployment, and maintenance.Upon completion of the planning, analysis, and design stages of the methodology, the student must submit those phases as a document to his or her Project Committee. Students who desire to graduate in May must submit this document by the second week of the previous fall semester, all others must submit by the second week of the previous Spring semester. For the student to proceed with the project, the student’s Project Committee must give written permission which indicates the first three phases have been successfully completed. This initial permission does not ensure final approval of the completed design and implementation.

There must be a public presentation of the work associated with the project. The annual Research Day sponsored by the Graduate School is an appropriate forum.

The student must submit a complete software design document consistent with the software methodology used, as well as the implementation, to his or her Project Committee. The Project Committee will transmit a written recommendation to the Dean of the Graduate School concerning the acceptability of the project.

Typically a project will require two semesters to complete

155 Final Year Project Ideas For Computer Science Students

Are you a computer science student about to embark on your final year project journey? If so, you’re in for an exciting and challenging ride! Your final year project is a chance to apply what you’ve learned throughout your academic journey and showcase your skills to potential employers. To help you get started, we’ve compiled a list of 155 final year project ideas for computer science students, presented in the simplest language possible.

150+ Final Year Project Ideas For Computer Science Students

Table of Contents

Web Development Projects:

• E-commerce Website : Create an online store with features like product catalog, shopping cart, and secure payment processing.
• Content Management System (CMS) : Build a user-friendly platform for managing website content.
• Blog Platform : Develop a blogging website with user profiles, comments, and likes.
• Event Management System : Design a system to manage and promote events.
• Portfolio Website : Create a website to showcase your own work and achievements.

Mobile App Development:

• Expense Tracker : Build an app to help users manage their finances.
• To-Do List App : Create a task management app with priority levels and reminders.
• Recipe App : Develop an app for sharing and discovering recipes.
• Fitness Tracker : Build an app to track workouts and nutrition.
• Weather App : Create an app that provides real-time weather forecasts.

Data Analysis and Machine Learning:

• Stock Market Predictor : Use historical data to predict stock prices.
• Sentiment Analysis : Analyze social media data to gauge public sentiment on a topic.
• Recommendation System : Build a system that suggests products or content based on user behavior.
• Healthcare Analytics : Analyze medical data to identify trends and improve patient care.
• Image Recognition : Develop an image recognition system for objects or faces.

Networking and Security:

• Network Monitoring Tool : Create a tool to monitor network traffic and detect anomalies.
• Intrusion Detection System (IDS) : Build a system to identify and respond to network intrusions.
• Secure Messaging App : Develop an encrypted messaging app for privacy-conscious users.
• Firewall Management : Create a firewall management tool with user-friendly controls.
• Password Manager : Build a secure password manager for storing and generating strong passwords.

Artificial Intelligence and Robotics:

• Chatbot : Create a chatbot that can answer user questions and engage in conversations.
• Autonomous Drone : Build a drone that can navigate and perform tasks autonomously.
• Gesture Recognition : Develop a system that recognizes hand gestures for controlling devices.
• AI-Based Game : Create a computer game with intelligent non-player characters (NPCs).
• Natural Language Processing (NLP) : Work on an NLP project like language translation or sentiment analysis.

Database Projects:

• Online Library System : Design a database system for managing library resources.
• Inventory Management : Create a database for tracking product inventory in a store.
• Student Information System : Develop a system for managing student records and grades.
• Hospital Management : Build a database system for hospital patient records and appointments.
• E-Voting System : Create an electronic voting system with secure database management.

Web Security:

• Cross-Site Scripting (XSS) Prevention : Develop a tool or technique to prevent XSS attacks on websites.
• SQL Injection Prevention : Create a system to protect databases from SQL injection attacks.
• Firewall Rules Analyzer : Build a tool that analyzes firewall rules for vulnerabilities.
• Secure Authentication : Work on improving user authentication methods for websites.
• Data Encryption : Develop a system for encrypting and decrypting sensitive data.

Augmented and Virtual Reality (AR/VR):

• AR Navigation App : Create an app that provides augmented reality navigation instructions.
• VR Game : Develop a virtual reality game or experience.
• Architectural Visualization : Design an AR/VR tool for visualizing architectural plans.
• Education in VR : Build an educational VR application for immersive learning.
• Medical Training Simulations : Create medical training simulations using AR/VR.

Internet of Things (IoT):

• Smart Home Automation : Build a system to control home appliances remotely.
• IoT-based Health Monitoring : Develop a device for monitoring vital signs and sending alerts.
• Smart Agriculture : Create a system for monitoring and controlling farm conditions.
• Traffic Management : Build a smart traffic management system using IoT devices.
• Environmental Monitoring : Create IoT sensors for monitoring air quality, water quality, etc.

Software Development Tools:

• Code Editor : Create a code editor with features like syntax highlighting and auto-completion.
• Version Control System : Build a version control system like Git.
• Bug Tracking System : Develop a tool for tracking and managing software bugs.
• Continuous Integration (CI) Pipeline : Design a CI/CD pipeline for automated software testing and deployment.
• IDE for a Specific Language : Create an integrated development environment (IDE) for a specific programming language.

Blockchain:

• Cryptocurrency Wallet : Build a digital wallet for managing cryptocurrencies.
• Supply Chain Tracking : Create a blockchain-based system for tracking the supply chain.
• Blockchain Voting System : Develop a secure online voting system using blockchain technology.
• Smart Contracts : Work on smart contracts for automating transactions.
• Blockchain-Based Authentication : Build a secure authentication system using blockchain.

Natural Language Processing (NLP):

• Language Translation Tool : Create a tool that translates text between languages.
• Chatbot for Customer Support : Develop an NLP-based chatbot for customer service.
• Text Summarization : Build a system that summarizes long texts or articles.
• Named Entity Recognition : Create a tool that identifies names, dates, and other entities in text.
• Speech Recognition : Work on a speech recognition system for converting spoken language into text.

Game Development:

• 2D Platformer Game : Create a classic 2D platformer game with levels and challenges.
• RPG Game : Develop a role-playing game with quests, characters, and a storyline.
• Multiplayer Online Game : Build a multiplayer game that can be played over the internet.
• VR Game : As mentioned earlier, create a virtual reality game.
• Augmented Reality Game : Design an AR game that combines the real world with virtual elements.

Robotics and Automation:

• Robotic Arm Control : Build a system for controlling a robotic arm for various tasks.
• Autonomous Robot : Create a robot that can navigate and perform tasks autonomously.
• Voice-Controlled Robot : Develop a robot that responds to voice commands.
• AI-Powered Robot : Work on a robot that can learn and adapt to different environments.
• Robotic Vacuum Cleaner : Build a robotic vacuum cleaner with obstacle avoidance.

Cloud Computing:

• Cloud-Based File Storage : Create a secure file storage system in the cloud.
• Serverless Computing : Develop applications using serverless computing platforms like – .
• Cloud-Based Machine Learning : Implement machine learning models in the cloud for scalability.
• Distributed Systems : Work on projects that involve distributed computing and data processing.
• Cloud Security : Develop tools or techniques for enhancing cloud security.

Cybersecurity:

• Vulnerability Scanner : Create a tool that scans networks or websites for vulnerabilities.
• Password Cracking Detection : Build a system to detect and prevent password cracking attempts.
• Phishing Detection : Develop a phishing detection system for emails and websites.
• Network Traffic Analysis : Analyze network traffic for signs of malicious activity.
• Malware Detection : Create a system that identifies and removes malware from systems.

Computer Vision:

• Facial Recognition System : Build a system that recognizes faces for security or authentication.
• Object Detection : Create a system that can identify and locate objects within images or videos.
• Traffic Sign Recognition : Develop a system that recognizes and interprets traffic signs.
• Gesture Recognition : As mentioned earlier, work on gesture recognition for human-computer interaction.
• Medical Image Analysis : Analyze medical images like X-rays or MRIs for diagnosis.

Data Visualization:

• Interactive Dashboard : Create an interactive dashboard for visualizing data.
• Geospatial Data Visualization : Visualize geographic data on maps.
• Real-time Data Visualization : Develop a system that updates data visualizations in real time.
• Stock Market Data Visualization : Visualize stock market trends and data.
• Healthcare Data Visualization : Visualize healthcare data for better decision-making.

Social Media and Networking:

• Social Media Analytics : Analyze social media data to gain insights into user behavior.
• Friend Recommendation System : Build a system that suggests friends or connections on social networks.
• Social Media Sentiment Analysis : Analyze sentiment on social media platforms.
• Online Dating Platform : Create a platform for online dating with matching algorithms.
• Social Networking App : Develop a new social networking app with unique features.

Human-Computer Interaction (HCI):

• User Interface Design : Work on improving the user interfaces of existing software.
• Voice User Interface (VUI) : Create a voice-controlled interface for a software application.
• Gestural User Interface : Develop a user interface that responds to gestures.
• Accessibility Tools : Build tools to make software more accessible to people with disabilities.
• Virtual Reality User Interface : Design a user interface for VR applications.
• Big Data Analytics : Analyze large datasets to extract valuable insights.
• Real-time Data Processing : Develop systems for processing real-time data streams.
• Data Warehousing : Create a data warehousing solution for storing and retrieving data.
• Big Data Visualization : Visualize big data in meaningful ways.
• Predictive Analytics : Use big data to build predictive models for various applications.

Internet Security:

• Secure File Transfer : Develop a secure file transfer protocol or application.
• Email Encryption : Create a system for encrypting email communications.
• Identity Verification : Build a system for secure online identity verification.
• Secure Online Payments : Work on enhancing the security of online payment systems.
• Network Security Audit : Develop tools for conducting security audits on computer networks.

Mobile Security:

• Mobile App Security Scanner : Create a tool to scan mobile apps for security vulnerabilities.
• Anti-Malware App : Develop a mobile app that detects and removes malware.
• Mobile Payment Security : Enhance the security of mobile payment apps.
• Secure Messaging App : As mentioned earlier, build a secure messaging app.
• Mobile Device Tracker : Create a tool for tracking and recovering lost or stolen mobile devices.

Software Testing:

• Automated Testing Framework : Develop a framework for automated software testing.
• Load Testing Tool : Create a tool for simulating heavy user loads on web applications.
• Code Coverage Analyzer : Build a tool to measure code coverage during testing.
• Bug Reporting System : Design a system for efficient bug reporting and tracking.
• Test Data Generation : Develop a tool for generating test data.
• 2D Game Engine : Create a game engine for developing 2D games.
• Physics Engine : Build a physics engine for realistic game physics.
• Game Level Design Tool : Develop a tool for designing game levels and environments.
• Multiplayer Game Server : Create a server for hosting multiplayer games.
• Game AI Framework : Design a framework for implementing game AI.
• Serverless API : Build a serverless API for deploying and managing APIs.
• Container Orchestration : Develop a system for orchestrating containers in the cloud.
• Cloud Cost Management : Create tools for monitoring and managing cloud infrastructure costs.
• Serverless Data Processing : Implement data processing workflows using serverless architecture.
• Cloud-based IoT : Build an IoT platform that leverages cloud services.
• IoT-Based Home Automation : Create a system to control home appliances and security using IoT.
• Smart City Solutions : Develop IoT solutions for enhancing urban living.
• IoT in Agriculture : Create IoT devices and systems for precision agriculture.
• Industrial IoT : Build IoT solutions for monitoring and optimizing industrial processes.
• IoT-Based Healthcare : Develop healthcare devices and systems using IoT.
• Text Generation : Create a system that generates human-like text based on input data.
• Language Translation : Work on improving machine translation systems.
• Chatbots for Specific Domains : Develop chatbots tailored to specific industries or topics.
• Speech-to-Text and Text-to-Speech : Build systems for converting spoken language to text and vice versa.
• Emotion Recognition in Text : Create a system that can detect emotions in written text.

Artificial Intelligence (AI):

• AI-Powered Personal Assistant : Develop a personal assistant like Siri or Alexa.
• AI-Based Game Opponents : Create intelligent AI opponents for computer games.
• AI in Healthcare : Build AI systems for diagnosing diseases or suggesting treatments.
• AI in Education : Create AI-based educational tools and platforms.
• AI in Finance : Work on AI applications in the financial industry.
• Robotic Arm for Surgery : Develop a robotic system for assisting surgeons.
• Autonomous Delivery Robot : Create a robot for delivering packages autonomously.
• Robotic Pet Companion : Build a robot designed to provide companionship to users.
• Robotic Exoskeleton : Develop an exoskeleton for assisting people with mobility challenges.
• Autonomous Cleaning Robot : Create a robot for cleaning and maintaining spaces.
• Blockchain-Based Supply Chain : Develop a blockchain solution for supply chain transparency.
• Blockchain Identity Verification : Create a system for secure identity verification using blockchain.
• Blockchain-Based Voting System : As mentioned earlier, work on a blockchain-based voting system.
• Blockchain for Intellectual Property : Use blockchain for protecting intellectual property rights.
• Blockchain in Education : Implement blockchain solutions for verifying educational credentials.

That’s quite a list of project ideas for computer science students! Remember, the key to a successful final year project is to choose something that genuinely interests you and aligns with your skills and career goals. So, take your time to explore these ideas, consult with your professors, and select a project that excites you. Good luck with your final year project, and may you succeed in your computer science journey!

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Top 50 Mini Project Ideas For Computer Science Engineers (Updated)

In the dynamic world of computer science, engineers are always on the lookout for exciting projects to enhance their skills. Mini projects serve as a fantastic way to apply theoretical knowledge in a practical setting. Whether you’re a budding programmer or an experienced developer, engaging in mini project ideas for computer science engineers can sharpen your problem-solving abilities and deepen your understanding of various concepts.

How To Choose Mini Project For CSE?

Table of Contents

Choosing a mini project for Computer Science Engineering (CSE) involves considering various factors to ensure it aligns with your interests, skill level, and learning objectives. Here’s a step-by-step guide on how to choose a mini project for CSE:

• Identify Your Interests: Reflect on your interests within the broad field of computer science. Are you passionate about software development, data analysis, cybersecurity, artificial intelligence, networking, or another specific area? Pick a project that matches what you like, so you stay excited and involved while working on it.
• Assess Your Skills: Evaluate your current skill level and expertise in different programming languages, technologies, and tools. Choose a project that challenges you but is also within your skill range. This ensures that you can effectively complete the project while also learning new concepts and techniques along the way.
• Consider Learning Objectives: Determine what you want to achieve through the mini project. Are you looking to deepen your understanding of a specific programming language, explore new technologies, or gain hands-on experience in a particular area of computer science? Choose a project that helps you meet your learning objectives and enhances your knowledge and skills accordingly.
• Review Project Ideas: Explore a variety of project ideas and brainstorm potential options. Consider browsing online resources, such as project repositories, forums, and blogs, for inspiration. Look for projects that are relevant, practical, and achievable within the given time frame.
• Evaluate Feasibility: Assess the feasibility of each project idea based on factors such as available resources, time constraints, and complexity. Choose a project that you can realistically complete given your available resources, including access to hardware, software, and technical support if needed.
• Set Clear Goals: Set clear and doable goals for your mini project, like what you want to achieve, what needs to be done, and when it should be finished. Divide your project into small tasks and checkpoints to see how far you’ve come and make sure you finish on time.
• Seek Guidance and Feedback: Ask your teachers, mentors, or friends for help. They can give you good advice and tell you what they think about your project idea. Discuss your goals, challenges, and potential solutions to refine your project concept and ensure its viability.
• Stay Flexible: Remain open to adjusting your project idea based on feedback, new insights, or changing circumstances. Be willing to adapt and iterate as needed to overcome challenges and achieve your desired outcomes.

By following these steps, you can effectively choose a mini project for CSE that aligns with your interests, goals, and skill level, allowing you to maximize your learning and development opportunities in the field of computer science.

Top 50 Mini Project Ideas For Computer Science Engineers: Category Wise

Software development.

• Personal portfolio website
• Blogging platform
• E-commerce website for a small business
• Task management app
• Weather forecast app
• Fitness tracking app
• Text editor with basic features
• Calculator application
• File management system
• Online quiz application

Data Science and Machine Learning

• COVID-19 data analysis and visualization
• Stock market trend prediction
• Social media sentiment analysis
• Spam email classifier
• Movie or book recommendation system
• Handwriting recognition system
• Image classification for object recognition
• Predicting house prices based on housing data
• Customer churn prediction for businesses
• Sentiment analysis of product reviews

Networking and Security

• Network protocol simulation (e.g., TCP/IP)
• Basic chat application using sockets
• File transfer protocol implementation
• Password manager application
• Network packet sniffer
• Intrusion detection system
• Network bandwidth monitor
• Simple VPN (Virtual Private Network) implementation
• Firewall rules management tool
• Network traffic analyzer

Artificial Intelligence

• Text summarization tool
• Chatbot for customer support
• Natural language processing for sentiment analysis
• Face recognition system
• Vehicle detection system for traffic monitoring
• Gesture recognition system for human-computer interaction
• Emotion recognition from facial expressions
• Music recommendation system
• Fraud detection system for financial transactions
• Speech recognition system

Web Development

• Online voting system
• Social networking site
• Online book rental system
• Online examination system
• Restaurant management system
• Online ticket booking system
• Content management system (CMS) for blogs
• Online banking system
• Real-time chat application
• Task scheduling application

How Do You Make A Mini Project in Computer Science?

Creating a mini project in computer science involves several steps, from ideation to implementation. Here’s a simplified guide on how to make a mini project:

Choose a Topic

• Identify an area of interest within computer science, such as software development, data science, networking, security, or artificial intelligence.
• Consider your skills, interests, and learning goals when selecting a topic for your mini project.

Define Objectives

• Clearly define the objectives and goals of your mini project. What do you want to achieve? What problem are you solving or what functionality are you implementing?

Plan Your Project

• Break down your project into smaller, manageable tasks or modules.
• Create a project timeline or schedule to allocate time for each task and ensure timely completion.

Research and Gather Resources

• Conduct research to gather information, resources, and tools relevant to your project.
• Explore online documentation, tutorials, and examples to understand concepts and technologies required for your project.

Design the Solution

• Design the architecture and components of your project.
• Create flowcharts, diagrams, or wireframes to visualize the structure and flow of your application or system.

Implement Your Project

• Start coding based on your project design and requirements.
• Follow best practices and coding standards to ensure readability, maintainability, and scalability of your code.

Test Your Project

• Test each component of your project to identify and fix any bugs or errors.
• Perform unit testing, integration testing, and system testing to ensure the functionality and reliability of your project.

Iterate and Improve

• Gather feedback from peers, mentors, or users to improve your project.
• Iterate on your project based on feedback and new insights to enhance its performance, usability, and user experience.

Document Your Project

• Document your project’s design, implementation, and testing process.
• Write clear and concise documentation to help others understand and use your project effectively.

Showcase Your Project

• Showcase your completed project through presentations, demos, or portfolio showcases.
• Share your project on online platforms , such as GitHub, to demonstrate your skills and accomplishments to potential employers or collaborators.

Reflect and Learn

• Reflect on your mini project experience and lessons learned.
• Identify areas for improvement and consider how you can apply your newfound knowledge and skills to future projects or endeavors.

By following these steps, you can successfully create mini project ideas for computer science engineers that not only enhances your skills and knowledge but also showcases your creativity and problem-solving abilities.

Mini projects offer a fantastic opportunity for computer science engineers to apply their knowledge and skills in practical scenarios.

Whether you’re interested in software development, data science, networking, cybersecurity, or artificial intelligence, there’s a wide range of exciting projects to explore.

By undertaking mini project ideas for computer science engineers, you can gain valuable experience, enhance your problem-solving abilities, and prepare yourself for future challenges in the field of computer science.

So, roll up your sleeves, pick a project that interests you, and embark on an exciting journey of learning and innovation!

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Universities Have a Computer-Science Problem

The case for teaching coders to speak French

Listen to this article

Produced by ElevenLabs and News Over Audio (NOA) using AI narration.

Updated at 5:37 p.m. ET on March 22, 2024

Last year, 18 percent of Stanford University seniors graduated with a degree in computer science, more than double the proportion of just a decade earlier. Over the same period at MIT, that rate went up from 23 percent to 42 percent . These increases are common everywhere: The average number of undergraduate CS majors at universities in the U.S. and Canada tripled in the decade after 2005, and it keeps growing . Students’ interest in CS is intellectual—culture moves through computation these days—but it is also professional. Young people hope to access the wealth, power, and influence of the technology sector.

That ambition has created both enormous administrative strain and a competition for prestige. At Washington University in St. Louis, where I serve on the faculty of the Computer Science & Engineering department, each semester brings another set of waitlists for enrollment in CS classes. On many campuses, students may choose to study computer science at any of several different academic outposts, strewn throughout various departments. At MIT, for example, they might get a degree in “Urban Studies and Planning With Computer Science” from the School of Architecture, or one in “Mathematics With Computer Science” from the School of Science, or they might choose from among four CS-related fields within the School of Engineering. This seepage of computing throughout the university has helped address students’ booming interest, but it also serves to bolster their demand.

Another approach has gained in popularity. Universities are consolidating the formal study of CS into a new administrative structure: the college of computing. MIT opened one in 2019. Cornell set one up in 2020. And just last year, UC Berkeley announced that its own would be that university’s first new college in more than half a century. The importance of this trend—its significance for the practice of education, and also of technology—must not be overlooked. Universities are conservative institutions, steeped in tradition. When they elevate computing to the status of a college, with departments and a budget, they are declaring it a higher-order domain of knowledge and practice, akin to law or engineering. That decision will inform a fundamental question: whether computing ought to be seen as a superfield that lords over all others, or just a servant of other domains, subordinated to their interests and control. This is, by no happenstance, also the basic question about computing in our society writ large.

When I was an undergraduate at the University of Southern California in the 1990s, students interested in computer science could choose between two different majors: one offered by the College of Letters, Arts and Sciences, and one from the School of Engineering. The two degrees were similar, but many students picked the latter because it didn’t require three semesters’ worth of study of a (human) language, such as French. I chose the former, because I like French.

An American university is organized like this, into divisions that are sometimes called colleges , and sometimes schools . These typically enjoy a good deal of independence to define their courses of study and requirements as well as research practices for their constituent disciplines. Included in this purview: whether a CS student really needs to learn French.

The positioning of computer science at USC was not uncommon at the time. The first academic departments of CS had arisen in the early 1960s, and they typically evolved in one of two ways: as an offshoot of electrical engineering (where transistors got their start), housed in a college of engineering; or as an offshoot of mathematics (where formal logic lived), housed in a college of the arts and sciences. At some universities, including USC, CS found its way into both places at once.

The contexts in which CS matured had an impact on its nature, values, and aspirations. Engineering schools are traditionally the venue for a family of professional disciplines, regulated with licensure requirements for practice. Civil engineers, mechanical engineers, nuclear engineers, and others are tasked to build infrastructure that humankind relies on, and they are expected to solve problems. The liberal-arts field of mathematics, by contrast, is concerned with theory and abstraction. The relationship between the theoretical computer scientists in mathematics and the applied ones in engineers is a little like the relationship between biologists and doctors, or physicists and bridge builders. Keeping applied and pure versions of a discipline separate allows each to focus on its expertise, but limits the degree to which one can learn from the other.

Read: Programmers, stop calling yourself engineers

By the time I arrived at USC, some universities had already started down a different path. In 1988, Carnegie Mellon University created what it says was one of the first dedicated schools of computer science. Georgia Institute of Technology followed two years later. “Computing was going to be a big deal,” says Charles Isbell, a former dean of Georgia Tech’s college of computing and now the provost at the University of Wisconsin-Madison. Emancipating the field from its prior home within the college of engineering gave it room to grow, he told me. Within a decade, Georgia Tech had used this structure to establish new research and teaching efforts in computer graphics, human-computer interaction, and robotics. (I spent 17 years on the faculty there, working for Isbell and his predecessors, and teaching computational media.)

Kavita Bala, Cornell University’s dean of computing, told me that the autonomy and scale of a college allows her to avoid jockeying for influence and resources. MIT’s computing dean, Daniel Huttenlocher, says that the speed at which computing evolves justifies the new structure.

But the computing industry isn’t just fast-moving. It’s also reckless. Technology tycoons say they need space for growth, and warn that too much oversight will stifle innovation. Yet we might all be better off, in certain ways, if their ambitions were held back even just a little. Instead of operating with a deep understanding or respect for law, policy, justice, health, or cohesion, tech firms tend to do whatever they want . Facebook sought growth at all costs, even if its take on connecting people tore society apart . If colleges of computing serve to isolate young, future tech professionals from any classrooms where they might imbibe another school’s culture and values—engineering’s studied prudence, for example, or the humanities’ focus on deliberation—this tendency might only worsen.

Read: The moral failure of computer scientists

When I raised this concern with Isbell, he said that the same reasoning could apply to any influential discipline, including medicine and business. He’s probably right, but that’s cold comfort. The mere fact that universities allow some other powerful fiefdoms to exist doesn’t make computing’s centralization less concerning. Isbell admitted that setting up colleges of computing “absolutely runs the risk” of empowering a generation of professionals who may already be disengaged from consequences to train the next one in their image. Inside a computing college, there may be fewer critics around who can slow down bad ideas. Disengagement might redouble. But he said that dedicated colleges could also have the opposite effect. A traditional CS department in a school of engineering would be populated entirely by computer scientists, while the faculty for a college of computing like the one he led at Georgia Tech might also house lawyers, ethnographers, psychologists, and even philosophers like me. Huttenlocher repeatedly emphasized that the role of the computing college is to foster collaboration between CS and other disciplines across the university. Bala told me that her college was established not to teach CS on its own but to incorporate policy, law, sociology, and other fields into its practice. “I think there are no downsides,” she said.

Mark Guzdial is a former faculty member in Georgia Tech’s computing college, and he now teaches computer science in the University of Michigan’s College of Engineering. At Michigan, CS wasn’t always housed in engineering—Guzdial says it started out inside the philosophy department, as part of the College of Literature, Science and the Arts. Now that college “wants it back,” as one administrator told Guzdial. Having been asked to start a program that teaches computing to liberal-arts students, Guzdial has a new perspective on these administrative structures. He learned that Michigan’s Computer Science and Engineering program and its faculty are “despised” by their counterparts in the humanities and social sciences. “They’re seen as arrogant, narrowly focused on machines rather than people, and unwilling to meet other programs’ needs,” he told me. “I had faculty refuse to talk to me because I was from CSE.”

In other words, there may be downsides just to placing CS within an engineering school, let alone making it an independent college. Left entirely to themselves, computer scientists can forget that computers are supposed to be tools that help people. Georgia Tech’s College of Computing worked “because the culture was always outward-looking. We sought to use computing to solve others’ problems,” Guzdial said. But that may have been a momentary success. Now, at Michigan, he is trying to rebuild computing education from scratch, for students in fields such as French and sociology. He wants them to understand it as a means of self-expression or achieving justice—and not just a way of making software, or money.

Early in my undergraduate career, I decided to abandon CS as a major. Even as an undergraduate, I already had a side job in what would become the internet industry, and computer science, as an academic field, felt theoretical and unnecessary. Reasoning that I could easily get a job as a computer professional no matter what it said on my degree, I decided to study other things while I had the chance.

I have a strong memory of processing the paperwork to drop my computer-science major in college, in favor of philosophy. I walked down a quiet, blue-tiled hallway of the engineering building. All the faculty doors were closed, although the click-click of mechanical keyboards could be heard behind many of them. I knocked on my adviser’s door; she opened it, silently signed my paperwork without inviting me in, and closed the door again. The keyboard tapping resumed.

The whole experience was a product of its time, when computer science was a field composed of oddball characters, working by themselves, and largely disconnected from what was happening in the world at large. Almost 30 years later, their projects have turned into the infrastructure of our daily lives. Want to find a job? That’s LinkedIn. Keep in touch? Gmail, or Instagram. Get news? A website like this one, we hope, but perhaps TikTok. My university uses a software service sold by a tech company to run its courses. Some things have been made easier with computing. Others have been changed to serve another end, like scaling up an online business.

Read: So much for ‘learn to code’

The struggle to figure out the best organizational structure for computing education is, in a way, a microcosm of the struggle under way in the computing sector at large. For decades, computers were tools used to accomplish tasks better and more efficiently. Then computing became the way we work and live. It became our culture, and we began doing what computers made possible, rather than using computers to solve problems defined outside their purview. Tech moguls became famous, wealthy, and powerful. So did CS academics (relatively speaking). The success of the latter—in terms of rising student enrollments, research output, and fundraising dollars—both sustains and justifies their growing influence on campus.

If computing colleges have erred, it may be in failing to exert their power with even greater zeal. For all their talk of growth and expansion within academia, the computing deans’ ambitions seem remarkably modest. Martial Hebert, the dean of Carnegie Mellon’s computing school, almost sounded like he was talking about the liberal arts when he told me that CS is “a rich tapestry of disciplines” that “goes far beyond computers and coding.” But the seven departments in his school correspond to the traditional, core aspects of computing plus computational biology. They do not include history, for example, or finance. Bala and Isbell talked about incorporating law, policy, and psychology into their programs of study, but only in the form of hiring individual professors into more traditional CS divisions. None of the deans I spoke with aspires to launch, say, a department of art within their college of computing, or one of politics, sociology, or film. Their vision does not reflect the idea that computing can or should be a superordinate realm of scholarship, on the order of the arts or engineering. Rather, they are proceeding as though it were a technical school for producing a certain variety of very well-paid professionals. A computing college deserving of the name wouldn’t just provide deeper coursework in CS and its closely adjacent fields; it would expand and reinvent other, seemingly remote disciplines for the age of computation.

Near the end of our conversation, Isbell mentioned the engineering fallacy, which he summarized like this: Someone asks you to solve a problem, and you solve it without asking if it’s a problem worth solving. I used to think computing education might be stuck in a nesting-doll version of the engineer’s fallacy, in which CS departments have been asked to train more software engineers without considering whether more software engineers are really what the world needs. Now I worry that they have a bigger problem to address: how to make computer people care about everything else as much as they care about computers.

This article originally mischaracterized the views of MIT’s computing dean, Daniel Huttenlocher. He did not say that computer science would be held back in an arts-and-science or engineering context, or that it needs to be independent.