dissertation topic in computer science

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

Free Webinar: How To Find A Dissertation Research Topic

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

Research Topic Kickstarter - Need Help Finding A Research Topic?

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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Home > CICS > CS > CS_DISS

Computer Science Department Dissertations Collection

Dissertations from 2023 2023.

An Introspective Approach for Competence-Aware Autonomy , Connor Basich, Computer Science

Foundations of Node Representation Learning , Sudhanshu Chanpuriya, Computer Science

Learning to See with Minimal Human Supervision , Zezhou Cheng, Computer Science

IMPROVING USER EXPERIENCE BY OPTIMIZING CLOUD SERVICES , Ishita Dasgupta, Computer Science

Automating the Formal Verification of Software , Emily First, Computer Science

Learning from Sequential User Data: Models and Sample-efficient Algorithms , Aritra Ghosh, Computer Science

Human-Centered Technologies for Inclusive Collection and Analysis of Public-Generated Data , Mahmood Jasim, Computer Science

Rigorous Experimentation For Reinforcement Learning , Scott M. Jordan, Computer Science

Towards Robust Long-form Text Generation Systems , Kalpesh Krishna, Computer Science

Emerging Trustworthiness Issues in Distributed Learning Systems , Hamid Mozaffari, Computer Science

TOWARDS RELIABLE CIRCUMVENTION OF INTERNET CENSORSHIP , Milad nasresfahani, Computer Science

Evidence Assisted Learning for Clinical Decision Support Systems , Bhanu Pratap Singh Rawat, Computer Science

DESIGN AND ANALYSIS OF CONTENT CACHING SYSTEMS , Anirudh Sabnis, Computer Science

Quantifying and Enhancing the Security of Federated Learning , Virat Vishnu Shejwalkar, Computer Science

Effective and Efficient Transfer Learning in the Era of Large Language Models , Tu Vu, Computer Science

Data-driven Modeling and Analytics for Greening the Energy Ecosystem , John Wamburu, Computer Science

Bayesian Structural Causal Inference with Probabilistic Programming , Sam A. Witty, Computer Science

LEARNING TO RIG CHARACTERS , Zhan Xu, Computer Science

GRAPH REPRESENTATION LEARNING WITH BOX EMBEDDINGS , Dongxu Zhang, Computer Science

Dissertations from 2022 2022

COMBINATORIAL ALGORITHMS FOR GRAPH DISCOVERY AND EXPERIMENTAL DESIGN , Raghavendra K. Addanki, Computer Science

MEASURING NETWORK INTERFERENCE AND MITIGATING IT WITH DNS ENCRYPTION , Seyed Arian Akhavan Niaki, Computer Science

Few-Shot Natural Language Processing by Meta-Learning Without Labeled Data , Trapit Bansal, Computer Science

Communicative Information Visualizations: How to make data more understandable by the general public , Alyxander Burns, Computer Science

REINFORCEMENT LEARNING FOR NON-STATIONARY PROBLEMS , Yash Chandak, Computer Science

Modeling the Multi-mode Distribution in Self-Supervised Language Models , Haw-Shiuan Chang, Computer Science

Nonparametric Contextual Reasoning for Question Answering over Large Knowledge Bases , Rajarshi Das, Computer Science

Languages and Compilers for Writing Efficient High-Performance Computing Applications , Abhinav Jangda, Computer Science

Controllable Neural Synthesis for Natural Images and Vector Art , Difan Liu, Computer Science

Probabilistic Commonsense Knowledge , Xiang Li, Computer Science

DISTRIBUTED LEARNING ALGORITHMS: COMMUNICATION EFFICIENCY AND ERROR RESILIENCE , Raj Kumar Maity, Computer Science

Practical Methods for High-Dimensional Data Publication with Differential Privacy , Ryan H. McKenna, Computer Science

Incremental Non-Greedy Clustering at Scale , Nicholas Monath, Computer Science

High-Quality Automatic Program Repair , Manish Motwani, Computer Science

Unobtrusive Assessment of Upper-Limb Motor Impairment Using Wearable Inertial Sensors , Brandon R. Oubre, Computer Science

Mixture Models in Machine Learning , Soumyabrata Pal, Computer Science

Decision Making with Limited Data , Kieu My Phan, Computer Science

Neural Approaches for Language-Agnostic Search and Recommendation , Hamed Rezanejad Asl Bonab, Computer Science

Low Resource Language Understanding in Voice Assistants , Subendhu Rongali, Computer Science

Enabling Daily Tracking of Individual’s Cognitive State With Eyewear , Soha Rostaminia, Computer Science

LABELED MODULES IN PROGRAMS THAT EVOLVE , Anil K. Saini, Computer Science

Reliable Decision-Making with Imprecise Models , Sandhya Saisubramanian, Computer Science

Data Scarcity in Event Analysis and Abusive Language Detection , Sheikh Muhammad Sarwar, Computer Science

Representation Learning for Shape Decomposition, By Shape Decomposition , Gopal Sharma, Computer Science

Metareasoning for Planning and Execution in Autonomous Systems , Justin Svegliato, Computer Science

Approximate Bayesian Deep Learning for Resource-Constrained Environments , Meet Prakash Vadera, Computer Science

ANSWER SIMILARITY GROUPING AND DIVERSIFICATION IN QUESTION ANSWERING SYSTEMS , Lakshmi Nair Vikraman, Computer Science

Dissertations from 2021 2021

Neural Approaches to Feedback in Information Retrieval , Keping Bi, Computer Science

Sociolinguistically Driven Approaches for Just Natural Language Processing , Su Lin Blodgett, Computer Science

Enabling Declarative and Scalable Prescriptive Analytics in Relational Data , Matteo Brucato, Computer Science

Neural Methods for Answer Passage Retrieval over Sparse Collections , Daniel Cohen, Computer Science

Utilizing Graph Structure for Machine Learning , Stefan Dernbach, Computer Science

Enhancing Usability and Explainability of Data Systems , Anna Fariha, Computer Science

Algorithms to Exploit Data Sparsity , Larkin H. Flodin, Computer Science

3D Shape Understanding and Generation , Matheus Gadelha, Computer Science

Robust Algorithms for Clustering with Applications to Data Integration , Sainyam Galhotra, Computer Science

Improving Evaluation Methods for Causal Modeling , Amanda Gentzel, Computer Science

SAFE AND PRACTICAL MACHINE LEARNING , Stephen J. Giguere, Computer Science

COMPACT REPRESENTATIONS OF UNCERTAINTY IN CLUSTERING , Craig Stuart Greenberg, Computer Science

Natural Language Processing for Lexical Corpus Analysis , Abram Kaufman Handler, Computer Science

Social Measurement and Causal Inference with Text , Katherine A. Keith, Computer Science

Concentration Inequalities in the Wild: Case Studies in Blockchain & Reinforcement Learning , A. Pinar Ozisik, Computer Science

Resource Allocation in Distributed Service Networks , Nitish Kumar Panigrahy, Computer Science

History Modeling for Conversational Information Retrieval , Chen Qu, Computer Science

Design and Implementation of Algorithms for Traffic Classification , Fatemeh Rezaei, Computer Science

SCALING DOWN THE ENERGY COST OF CONNECTING EVERYDAY OBJECTS TO THE INTERNET , Mohammad Rostami, Computer Science

Deep Learning Models for Irregularly Sampled and Incomplete Time Series , Satya Narayan Shukla, Computer Science

Traffic engineering in planet-scale cloud networks , Rachee Singh, Computer Science

Video Adaptation for High-Quality Content Delivery , Kevin Spiteri, Computer Science

Learning from Limited Labeled Data for Visual Recognition , Jong-Chyi Su, Computer Science

Human Mobility Monitoring using WiFi: Analysis, Modeling, and Applications , Amee Trivedi, Computer Science

Geometric Representation Learning , Luke Vilnis, Computer Science

Understanding of Visual Domains via the Lens of Natural Language , Chenyun Wu, Computer Science

Towards Practical Differentially Private Mechanism Design and Deployment , Dan Zhang, Computer Science

Audio-driven Character Animation , Yang Zhou, Computer Science

Dissertations from 2020 2020

Noise-Aware Inference for Differential Privacy , Garrett Bernstein, Computer Science

Motion Segmentation - Segmentation of Independently Moving Objects in Video , Pia Katalin Bideau, Computer Science

An Empirical Assessment of the Effectiveness of Deception for Cyber Defense , Kimberly J. Ferguson-Walter, Computer Science

Integrating Recognition and Decision Making to Close the Interaction Loop for Autonomous Systems , Richard Freedman, Computer Science

Improving Reinforcement Learning Techniques by Leveraging Prior Experience , Francisco M. Garcia, Computer Science

Optimization and Training of Generational Garbage Collectors , Nicholas Jacek, Computer Science

Understanding the Dynamic Visual World: From Motion to Semantics , Huaizu Jiang, Computer Science

Improving Face Clustering in Videos , SouYoung Jin, Computer Science

Reasoning About User Feedback Under Identity Uncertainty in Knowledge Base Construction , Ariel Kobren, Computer Science

Learning Latent Characteristics of Data and Models using Item Response Theory , John P. Lalor, Computer Science

Higher-Order Representations for Visual Recognition , Tsung-Yu Lin, Computer Science

Learning from Irregularly-Sampled Time Series , Steven Cheng-Xian Li, Computer Science

Dynamic Composition of Functions for Modular Learning , Clemens GB Rosenbaum, Computer Science

Improving Visual Recognition With Unlabeled Data , Aruni Roy Chowdhury, Computer Science

Deep Neural Networks for 3D Processing and High-Dimensional Filtering , Hang Su, Computer Science

Towards Optimized Traffic Provisioning and Adaptive Cache Management for Content Delivery , Aditya Sundarrajan, Computer Science

The Limits of Location Privacy in Mobile Devices , Keen Yuun Sung, Computer Science

ALGORITHMS FOR MASSIVE, EXPENSIVE, OR OTHERWISE INCONVENIENT GRAPHS , David Tench, Computer Science

System Design for Digital Experimentation and Explanation Generation , Emma Tosch, Computer Science

Performance Evaluation of Classical and Quantum Communication Systems , Gayane Vardoyan, Computer Science

Probabilistic Inference with Generating Functions for Population Dynamics of Unmarked Individuals , Kevin Winner, Computer Science

Computational Approaches to Assisting Patients' Medical Comprehension from Electronic Health Records , Jiaping Zheng, Computer Science

Dissertations from 2019 2019

Neural Generative Models and Representation Learning for Information Retrieval , Qingyao Ai, Computer Science

Poetry: Identification, Entity Recognition, and Retrieval , John J. Foley IV, Computer Science

FROM OPTIMIZATION TO EQUILIBRATION: UNDERSTANDING AN EMERGING PARADIGM IN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING , Ian Gemp, Computer Science

Energy-Aware Algorithms for Greening Internet-Scale Distributed Systems Using Renewables , Vani Gupta, Computer Science

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Which topics are best for thesis in Computer Science?

Are you on the lookout for compelling dissertation topics within the realm of computer science? As technology continues to advance, the field of computer science undergoes constant evolution. If you’ve committed to this dynamic field, allow us to guide you in discovering suitable dissertation topics in computer science and crafting research proposals. Explore our curated […]

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Some Computer Science Dissertation Topics

Here are the best computer science dissertation topics for master’s and undergraduate students.

Ways to improve open web Architecture – a literature review.
A review of the development of the tracking app on the phone and how it has benefited anti-theft procedures.
An analysis of the development of JAVA programs for the Applied financial system and its benefits for effective financial management.
Web use in the library and how it has contributed to knowledge management.
An analysis of the evolution of digital libraries and how technology is aiding in education management in the 21st.
What is the role of IT in smart business management strategies?
An examination of the uses of computer systems in schools and colleges in developed countries.
To study the Integrating of multimedia and the web into language planning and measure the impact of applications on language use.
To explore the use of e-marketing services and how it has benefited retail businesses.
The examination of the role of Online learnings for e-commerce business – a case analysis.
How to enhance human computing interaction by using artificial intelligence?
An evaluation of how to use an intelligent database to store the speed limits.
Observe individual activities on social media platforms and these have influenced their personalities.
To observe the use of websites by individuals on social media and how businesses are benefiting from it.
To study the Importance of computer science studies in daily life, take Generation Y and Z.
How is computer science making human life easier? A systematic literature reviews.
To examine the impact of cyberinfrastructure on the marketing objectives of a retail business
To study the easiest and tricky way to earn money on the web.
To find out strategies to enhance the information-seeking behavior and retrieval.
To study the change of nature in the web environment conduct a review of the past 10 years.
To analyze the use of cloud computing and its benefits for businesses in this era of digitalization.
Different characteristics of cloud computing – A systematic literature review.
An analysis of semantic web and its role and development.
Why is the semantic web considered the next big thing in the field of communication?
To study the use of MANET on VANET – a comparative analysis.
To study the process of Data mining and how it benefits data management and knowledge management in companies.
Study the use of Data mining in the Genetic Algorithm in the business field.
What are the advantages and disadvantages of data mining?
What is Artificial intelligence in the field of computer science?
Study the use of image processing in computer science.
What is the main purpose of image processing?
To study quantum computing techniques and their advantages and limitations.
To study the use of Bioinformatics – a theoretical analysis.
Web application to assist in preparing for ABET accreditation.
To study the relationship between Genotype and Phenotype – a literature review.
What are the challenges faced by computer studies students in the US market?
An analysis of the scope of computer science studies for future generations.
To explore the best password management applications – a comparative study.
To study the implementation of dart matches analysis – a literature review.
What security issues and challenges do people usually have to deal with?
To evaluate the solutions related to cloud computing for e-commerce businesses.
To study the concept of fuzzy logic controller design for intelligent robots.
What is cryptography? A theoretical analysis of the concept and its role.
Impact of covid 19 on computer science and advancement of technology.
How is the world moving towards computer rather than physical interaction?
To analyze the process of data warehousing and data management.
To study the use of data warehousing in the financial sector – a case analysis.
To study the concept of the interconnection of various devices.
To study the use of IoT in the agriculture sector in the context of developing countries.
To study the use of big data in computer science.

In conclusion, embarking on a journey within the realm of computer science dissertation topics opens doors to boundless opportunities for exploration and innovation. As technology continues to advance at a rapid pace, the significance of research in this field becomes increasingly evident.

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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

Computer Science Dissertation Topics

Dissertations are one of the main pieces of work students undertake at university and they provide you with an opportunity to work independently and on something that really interests you. It’s easier to research essay questions and assignment topics that have been set for you, but it can be difficult to decide what to do when you have been given some freedom. There are so many areas that you could focus on when it comes to your computing dissertation, so we have come up with a range of original topics that might help to narrow down your interest:

Hardware, Network and Security Dissertation Topics

Software, programming and algorithm dissertation topics, information systems – computer science dissertation topics.

Computer Science is usually defined as the study of computers and technological systems. It also refers to the theories and practices adopted to reinforce Information Technology (IT). In contrast to computer or electrical engineers, computer scientists often deal with software programs, application evaluation, and programming languages. Major areas of study within the field of Computer Science include project management, artificial intelligence, computer network or systems, security, information systems, and the virtualisation of computer interfaces. Dissertation topics related to this field include:

A survey of the different technologies and algorithms for parsing and indexing multimedia databases.
How to visualise text categorisation with complex hierarchal structures and machine learning?
What are the different tools and techniques in software requirements understanding in the United Kingdom?
Conducting autonomous navigation within both indoor and outdoor environments and settings.
How to improve the value of inter-organisational knowledge management using IT?
Intelligent Marketing: Applying the concepts and methods of artificial intelligence in advertising & marketing process.
Computing a virtual model of an environment using an autonomous mobile robot.
How to identify the cybersecurity challenges of adopting automated vehicles in the United Kingdom?
How to identify the best approach to perform successful System-Level Testing of Distributed Systems.
What are the analysis and design requirements for a Next Generation Software Release Management System?
How to design a cloud-based Information System for an oil storage company based on Internet Technologies?
How to identify the requirements of Enterprise Content Management System for a software development company?
How to determine the various underlying factors that have significant impact on the information systems development process?
Investigation of ‘agile project management methods’ risk management evaluation and project management tools that integrate risk analysis into project management practices.
How to effectively implement risk approaches during software development process to prevent unsuccessful implementations?
What are the contemporary challenges/ issues in database design and information systems development?
Effectively implementing Bio-informatics to improve the provision of healthcare services in the United Kingdom.

Network security refers to all activities that are designed to protect the usability and reliability of organizations’ information and network structure, including software and hardware security measures and technologies. Efficient network security measures would include monitoring access to a network, while also scanning for potential threats or attacks, and preventing malicious activities on secured networks. Ultimately, network security is concerned with the security of an organisation’s information resources and computing assets. More dissertation topics related to hardware, network and security include:

Conducting a test lab for the performance analysis of TCP over Ethernet LANs on Windows operating systems.
Potential Privacy and Security Risks when authenticating on the Internet with Electronic ID cards.
How to prevent relay attacks and improve the security of smart card network transmissions?
What are the different security mechanisms in IEEE 802.11-based WLANs?
How to design efficient Intrusion Detection System for 4G networks
Explore the use of intrusion detection systems for intelligent analysis of data across multiple gateways.
How to develop a secure runtime/programming environment for studying the behaviour of malicious botnets and network worms
Analysis of network security using a programmatic approach.
What are the different strategic and methodological approaches for the development of ICT systems?
How to design and implement a distributed file sharing system used for supporting content mobility and disconnection tolerant communication?
How to design a secure, scalable and component-based Network Monitoring tool using struts and hibernates.
Scalable Router placement in software-defined networks.
An evaluation framework for secured routing in structured peer-to-peer (overlay) networks.
What are the issues for coordinated transmission techniques in next generation 5G wireless networks?
Performance studies of VoIP over Wireless and Ethernet LANs?
What is the impact of signal strength on Wi-Fi link throughput using propagation measurements?
Network Traffic Anomaly Detection using Software Defined Networking
How to secure data sharing in P2P (Peer-to-Peer) and Wi-Fi networks
How to apply database technologies for managing network data?
Fault recovery and redundancy in real-time wireless networking systems
Fault recovery and redundancy in 4G wireless networking systems.
Anonymous routing based on characteristics protocol
Planning for secure and dependable 4th generation wireless networks.
Using dynamic proxies to support RMI in a mobile environment.
A policy creation and enforcement environment for an IP network.
Real Time 3D motion tracking for interactive computer simulations Peer-to-peer live streaming and Video on Demand Design Issues and Challenges?
Using Humans as Cyber security sensors (HAASS) for the Internet of Things.
Large-scale automatic classification for phishing network attacks.
Enforcing Network Access Control through Security Policy Management.

Computer software, or any other types of software, is a general term used to describe a collection of computer programs, procedures and documentation that perform tasks or activities on a computer system. The term includes application software, such as word processors or dynamic websites, which perform productive tasks for users, system software such as operating systems, which interface with hardware to provide the necessary services for application software, database organisers to deal with big data and middleware which controls and co-ordinates distributed systems. Here are some original and relevant dissertation topics on software, programming and algorithm:

Development of web based document management system by using markup languages like J2EE, XML and Microsoft SQL Server
Development of room scheduling and work mapping system using software frameworks like Microsoft .NET Framework
Implementation and evaluation of optimal algorithm for computing association rules in certain environment
Implementation and evaluation of optimal algorithm for generating clusters
Implementation and evaluation of optimal algorithm for generating optimal and near optimal classification trees
Implementation and evaluation of heuristic algorithm for computing association rules
Implementation and evaluation of heuristic algorithm for generating clusters
Implementation and evaluation of heuristic algorithm for generating optimal and near optimal classification trees
Different techniques for designing intelligent interfaces for database systems, which provide a paradigm for programming databases without the knowledge of SQL and tables
Fault-Tolerant Routing in interconnection networks with multiple passes and fixed control variables
Fault-Tolerance analysis of sorting networks
Analysis, design and implementation of web services security framework
Hardware and/or high speed computer arithmetic using the residue number system
Implementation and evaluation of fast algorithms for One-Way Hashing Functions
Different techniques for testing embedded software systems
Methods to design a dynamic proxy based architecture to support distributed java objects in a mobile environment
Modular data serialization and mobile code
Various ways to improve Open Web Architectures
An adaptive web-based learning environment
Transportation (Bus/Car/Taxi) tracking service: Design and implementation of a device independent passenger information system
Development and evaluation of a scalable, fault tolerant telecommunications system using EJB and related technologies cryptographic access control for a network file system.
Event-based middleware for collaborative ad hoc applications
Proactive persistent agents – using situational intelligence to create support characters in character-centric computer games
Develop Java Applets to investigate the feasibility of designing objects to be manufactured by specification through individual users via the web
Development of distributed software environment by using Java RMI or alternative Java technologies, where users can work collaboratively on a project via the internet
Develop Java Programs for Applied Financial Systems like stock markets
Develop Web systems (HTML, CSS, JavaScript) to structure intelligent rental car booking system
Develop exercise-workout tracking app on Android/iOS

The term information system sometimes refers to a system of persons, data records and activities that process the data and information in an organisation, and it includes the organisation’s manual and automated processes. It can also include the technical aspect of HCI or human computer interaction. Computer-based information systems are the field of study for information technology, elements of which are sometimes called an “information system” as well. Dissertation topics on information systems include:

Challenges of building information systems for large healthcare like NHS UK
E-recruitment standards: challenges and future directions
Challenges and opportunities in migrating to web-based information services
Change management on the web environment
Changing nature of web space requirements
An analysis of collaborative social network tools for the gathering and classification of information from young people/middle/old aged people
Government policies toward adoption and diffusion of ICT, including e-government services and high-speed Internet access for household consumers/citizens in United Kingdom
Impact of e-publishing on the future of libraries
Impact of the web on library users
Implementing a new integrated information system in the library environment
Impact of full-text databases on search engine services
Impact of full-text databases on shopping cart users
Impact of Internet and cyber infrastructure on jobs and income in UK
Impact of Internet and Cyber infrastructure on marketing and marketing users in the United Kingdom
Implications for information seeking behaviour and retrieval
Usage of scientific innovation and information society by students in schools
Usage of scientific innovation and information society by graduation (both undergrad and postgrad) students
Integrating multimedia and the web into language planning and measuring the impact of applications on language use
Internet-based services, products, technologies and their impact on e-marketing, service, and utilisation: challenges and/or methodology to meet patron needs as marketing campaigns migrate to a digital/virtual environment
Different models of e-marketing services with the use of computers, networks, and the Internet.
Building Information System for e-learning in educational institutes in UK
Managing and tracking traffic fines by using big data analysis
Tracking over-speeding by using speed camera (using an intelligent database to store speed limits)
Improving HCI (human-computer interaction) by using AI (artificial intelligence) systems on mobile devices
Improving HCI (human-computer interaction) by using AI (artificial intelligence) systems on personal computers (laptops or desktops)
Monitoring an individual’s behaviour over social media like Facebook, Twitter etc. and develop patterns
Monitoring a young person’s usage and behaviour over social media like Facebook, Twitter etc. and develop patterns

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?

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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Home » Blog » Dissertation » Topics » Information Technology » Computer Science » 80 Computer Science Research Topics

80 Computer Science Research Topics

FacebookXEmailWhatsAppRedditPinterestLinkedInWelcome to Computer Science, a dynamic landscape where innovation and technology converge to shape the present and forge the path to the future. In an era driven by digital transformation, the significance of Computer Science resonates across industries, research endeavours, and everyday experiences. This post is a comprehensive gateway to a world of research possibilities, […]

Welcome to Computer Science, a dynamic landscape where innovation and technology converge to shape the present and forge the path to the future. In an era driven by digital transformation, the significance of Computer Science resonates across industries, research endeavours, and everyday experiences.

This post is a comprehensive gateway to a world of research possibilities, offering an expansive selection of distinctive research topics within Computer Science. These topics, from artificial intelligence and cybersecurity to software engineering and data science, are designed to ignite your curiosity and serve as catalysts for your scholarly voyage.

A List Of Potential Research Topics In Computer Science:

AI in Legal Research and Contract Analysis.
Reinforcement Learning in Autonomous Systems.
Evolutionary Algorithms for Solving Complex Optimization Problems.
Future Prospects of Quantum Machine Learning.
Challenges and Opportunities in Big Data Analytics for Business Insights.
Exploring AI in Video Game Development and Virtual Reality.
Improving Data Security in Cloud Computing Environments.
Impact of 5G Technology on Internet of Things (IoT) Devices.
Natural Language Understanding and the Quest for Conversational AI.
Bioinformatics: Analyzing Genomic Data for Medical Diagnostics.
The Ethical Implications of AI in Biometric Data Analysis.
Advancements in Natural Language Generation for Chatbots.
AI in Music Composition and Creativity.
AI and Machine Learning for Financial Forecasting and Stock Market Analysis.
Smart Cities and IoT: Transforming Urban Living.
Cognitive Computing and Its Role in Enhancing Decision-Making Processes.
Future of Cloud Computing: Trends and Innovations.
Blockchain Technology’s Impact on Supply Chain Management and Transparency.
Human-AI Collaboration in Healthcare Diagnosis.
AI in Education: Personalized Learning and Intelligent Tutoring Systems.
AI for Drug Discovery: Accelerating Pharmaceutical Research.
The Intersection of AI and Ethics in Autonomous Vehicles.
Future of Quantum Computing: Scalability and Practical Applications.
Quantum Computing and Climate Modeling.
Ethical Considerations in AI: Bias Detection and Mitigation in Machine Learning.
Data Privacy and Protection: Novel Approaches for Secure Data Sharing in Cloud Environments.
Human-Centric Computing: Designing Systems for Enhanced User Experience.
Robotics and Automation in Manufacturing: Enhancing Efficiency and Precision.
Leveraging Machine Learning for Predictive Healthcare Analytics.
Cloud-Native Application Development: Benefits and Challenges.
Augmented Reality and Virtual Reality: Transforming Education and Training.
Cybersecurity Challenges in the Age of IoT.
Humanoid Robots and Their Role in Elderly Care.
Sustainable Computing: Green Technologies for Energy-Efficient Data Centers.
Deep Learning Approaches for Medical Image Analysis and Disease Diagnosis.
Human-Computer Interaction: Designing Intuitive User Interfaces for Elderly Users.
The Intersection of AI and Creativity: Generating Art and Music.
The Role of Data Science in Understanding Climate Change Patterns.
Exploring the Ethics of AI in Decision-Making and Bias Prevention.
Software Testing Automation: Strategies for Efficient Bug Detection and Resolution.
Data Mining Techniques for Customer Behavior Analysis.
Robotic Process Automation: Streamlining Business Processes.
Challenges in Interpretable AI and Model Transparency.
Ethical AI and Bias Mitigation in Facial Recognition Systems.
The Impact of AI on Journalism and Media.
Quantum Machine Learning: Merging Quantum Computing with AI Algorithms.
Enhancing Natural Language Processing Models for Multilingual Sentiment Analysis.
Exploring Quantum Computing Algorithms for Complex Optimization Problems.
Quantum Computing in Drug Discovery: Accelerating Molecular Simulations.
Exploring the Potential of Edge Computing in Real-Time Data Processing.
AI-Driven Personalized Marketing: Targeting and Customer Engagement.
Quantum Computing and Cryptography: Threats and Solutions.
Natural Language Processing for Emotion Analysis and Sentiment Detection.
Cybersecurity Challenges in the Era of the Internet of Things (IoT).
Challenges and Solutions in Edge Computing Security.
Exploring Quantum Cryptography for Unbreakable Data Encryption.
Advancements in Computer Vision: Object Detection and Recognition.
Evolutionary Robotics: Simulating Evolution in Robotic Systems.
Enhancing Cybersecurity with Biometric Authentication.
AI-Enhanced Natural Disaster Prediction and Management.
Cybersecurity in Critical Infrastructure: Protecting Against Cyber Threats.
Edge AI: Processing Data at the Source for Speed and Efficiency.
Advances in Natural Language Generation for Content Creation.
AI in Healthcare: Diagnosing Diseases and Personalized Treatment Plans.
Privacy-Preserving Machine Learning: Techniques and Concerns.
AI and Robotics in Healthcare: Surgical Automation and Assistance.
AI in Supply Chain Management: Optimization and Efficiency.
Intelligent Virtual Assistants: Applications and Future Prospects.
Explainable AI: Making Complex Algorithms Understandable to Humans.
Data Science for Social Good: Addressing Societal Challenges.
Neural Networks and Their Applications in Speech Recognition.
Quantum Computing Algorithms for Optimization and Simulation.
AI-Powered Fraud Detection and Prevention in Financial Transactions.
Robotics in Space Exploration: Challenges and Opportunities.
AI-Powered Language Translation and Cross-Cultural Communication.
AI in Agriculture: Precision Farming and Crop Management.
Ethical Considerations in Autonomous Systems and Robotic Ethics.
Internet of Things (IoT) Security: Challenges and Countermeasures.
Quantum Computing for Financial Portfolio Optimization.
Exploring the Role of AI in Environmental Monitoring.

In conclusion, these unique computer science research topics include AI, data science, cybersecurity, and more. Let these spark your academic journey, driving you to explore uncharted territories and contribute to the evolving landscape. Use these as a springboard for your thesis or scholarly pursuits, as your insights can redefine human knowledge and shape the future.

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Computer Science Dissertations and Theses

Theses/dissertations from 2023 2023.

Seeing in the Dark: Towards Robust Pedestrian Detection at Nighttime , Afnan Althoupety (Dissertation)

A Deep Hierarchical Variational Autoencoder for World Models in Complex Reinforcement Learning Environments , Sriharshitha Ayyalasomayajula (Thesis)

Toward Efficient Rendering: A Neural Network Approach , Qiqi Hou (Dissertation)

Energy Auction with Non-Relational Persistence , Michael Ramez Howard (Thesis)

Implementing a Functional Logic Programming Language via the Fair Scheme , Andrew Michael Jost (Dissertation)

Multi-Agent Deep Reinforcement Learning for Radiation Localization , Benjamin Scott Totten (Thesis)

Theses/Dissertations from 2022 2022

Using Intrinsically-Typed Definitional Interpreters to Verify Compiler Optimizations in a Monadic Intermediate Language , Dani Barrack (Thesis)

An Automated Zoom Class Session Analysis Tool to Improve Education , Jack Arlo Cannon II (Thesis)

Scaling EPA-RIMM with Multicore System Management Interrupt Handlers , Alexander K. Freed (Thesis)

Unpaired Style Transfer Conditional Generative Adversarial Network for Scanned Document Generation , David Jonathan Hawbaker (Thesis)

Toward Analyzing the Diversity of Extractive Summaries , Aaron David Hudson (Thesis)

Making Curry with Rice: An Optimizing Curry Compiler , Steven Libby (Dissertation)

Domain Knowledge as Motion-Aware Inductive Bias for Deep Video Synthesis: Two Case Studies , Long Mai (Dissertation)

Theses/Dissertations from 2021 2021

Efficient Neuromorphic Algorithms for Gamma-Ray Spectrum Denoising and Radionuclide Identification , Merlin Phillip Carson (Thesis)

Storing Intermediate Results in Space and Time: SQL Graphs and Block Referencing , Basem Ibrahim Elazzabi (Dissertation)

Automated Test Generation for Validating SystemC Designs , Bin Lin (Dissertation)

Forecasting Optimal Parameters of the Broken Wing Butterfly Option Strategy Using Differential Evolution , David Munoz Constantine (Thesis)

Situate: An Agent-Based System for Situation Recognition , Max Henry Quinn (Dissertation)

Theses/Dissertations from 2020 2020

Multiple Diagram Navigation , Hisham Benotman (Dissertation)

Smart Contract Vulnerabilities on the Ethereum Blockchain: a Current Perspective , Daniel Steven Connelly (Thesis)

Extensible Performance-Aware Runtime Integrity Measurement , Brian G. Delgado (Dissertation)

Novel View Synthesis - a Neural Network Approach , Hoang Le (Dissertation)

Exploring the Potential of Sparse Coding for Machine Learning , Sheng Yang Lundquist (Dissertation)

Workflow Critical Path: a Data-Oriented Path Metric for Holistic HPC Workflows , Daniel D. Nguyen (Thesis)

Novel View Synthesis in Time and Space , Simon Niklaus (Dissertation)

Balancing Security, Performance and Deployability in Encrypted Search , David Joel Pouliot (Dissertation)

Theses/Dissertations from 2019 2019

A Secure Anti-Counterfeiting System using Near Field Communication, Public Key Cryptography, Blockchain, and Bayesian Games , Naif Saeed Alzahrani (Dissertation)

Spectral Clustering for Electrical Phase Identification Using Advanced Metering Infrastructure Voltage Time Series , Logan Blakely (Thesis)

Local Radiance , Scott Peter Britell (Dissertation)

Correct-by-Construction Typechecking with Scope Graphs , Katherine Imhoff Casamento (Thesis)

Versatile Binary-level Concolic Testing , Bo Chen (Dissertation)

Crumpled and Abraded Encryption: Implementation and Provably Secure Construction , Scott Sherlock Griffy (Thesis)

Knowing Without Knowing: Real-Time Usage Identification of Computer Systems , Leila Mohammed Hawana (Thesis)

Design and Experimental Evaluation of DeepMarket: an Edge Computing Marketplace with Distributed TensorFlow Execution Capability , Soyoung Kim (Thesis)

Localizing Little Landmarks with Transfer Learning , Sharad Kumar (Thesis)

Context-Aware Wi-Fi Infrastructure-based Indoor Positioning Systems , Huy Phuong Tran (Dissertation)

Theses/Dissertations from 2018 2018

Bounding Box Improvement with Reinforcement Learning , Andrew Lewis Cleland (Thesis)

Sensing Building Structure Using UWB Radios for Disaster Recovery , Jeong Eun Lee (Dissertation)

Annotation-Enabled Interpretation and Analysis of Time-Series Data , Niveditha Venugopal (Thesis)

EPA-RIMM-V: Efficient Rootkit Detection for Virtualized Environments , Tejaswini Ajay Vibhute (Thesis)

Theses/Dissertations from 2017 2017

Improved Scoring Models for Semantic Image Retrieval Using Scene Graphs , Erik Timothy Conser (Thesis)

Refining Bounding-Box Regression for Object Localization , Naomi Lynn Dickerson (Thesis)

Fully Generic Programming Over Closed Universes of Inductive-Recursive Types , Larry Diehl (Dissertation)

Communicating at Terahertz Frequencies , Farnoosh Moshirfatemi (Dissertation)

Designing In-Headset Authoring Tools for Virtual Reality Video , Cuong Nguyen (Dissertation)

Certifying Loop Pipelining Transformations in Behavioral Synthesis , Disha Puri (Dissertation)

Power-Aware Datacenter Networking and Optimization , Qing Yi (Dissertation)

Theses/Dissertations from 2016 2016

Identifying Relationships between Scientific Datasets , Abdussalam Alawini (Dissertation)

Information Representation and Computation of Spike Trains in Reservoir Computing Systems with Spiking Neurons and Analog Neurons , Amin Almassian (Thesis)

Investigations of an "Objectness" Measure for Object Localization , Lewis Richard James Coates (Thesis)

Image Stitching: Handling Parallax, Stereopsis, and Video , Fan Zhang (Dissertation)

Theses/Dissertations from 2015 2015

Novel Methods for Learning and Adaptation in Chemical Reaction Networks , Peter Banda (Dissertation)

Post-silicon Functional Validation with Virtual Prototypes , Kai Cong (Dissertation)

Novel Cryptographic Primitives and Protocols for Censorship Resistance , Kevin Patrick Dyer (Dissertation)

Hardware/Software Interface Assurance with Conformance Checking , Li Lei (Dissertation)

Leveraging Contextual Relationships Between Objects for Localization , Clinton Leif Olson (Thesis)

The Performance of Random Prototypes in Hierarchical Models of Vision , Kendall Lee Stewart (Thesis)

Tweakable Ciphers: Constructions and Applications , Robert Seth Terashima (Dissertation)

Scalable Equivalence Checking for Behavioral Synthesis , Zhenkun Yang (Dissertation)

Theses/Dissertations from 2014 2014

The Nax Language: Unifying Functional Programming and Logical Reasoning in a Language based on Mendler-style Recursion Schemes and Term-indexed Types , Ki Yung Ahn (Dissertation)

Using Spammers' Computing Resources for Volunteer Computing , Thai Le Quy Bui (Thesis)

Towards Constructing Interactive Virtual Worlds , Francis Chang (Dissertation)

System-wide Performance Analysis for Virtualization , Deron Eugene Jensen (Thesis)

Advances in Piecewise Smooth Image Reconstruction , Ralf Juengling (Dissertation)

Interpretable Machine Learning and Sparse Coding for Computer Vision , Will Landecker (Dissertation)

Optimizing Data Movement in Hybrid Analytic Systems , Patrick Michael Leyshock (Dissertation)

Ranked Similarity Search of Scientific Datasets: An Information Retrieval Approach , Veronika Margaret Megler (Dissertation)

Using GIST Features to Constrain Search in Object Detection , Joanna Browne Solmon (Thesis)

The Role of Prototype Learning in Hierarchical Models of Vision , Michael David Thomure (Dissertation)

Theses/Dissertations from 2013 2013

Object Detection and Recognition in Natural Settings , George William Dittmar (Thesis)

Trust-but-Verify: Guaranteeing the Integrity of User-generated Content in Online Applications , Akshay Dua (Dissertation)

Equivalence Checking for High-Assurance Behavioral Synthesis , Kecheng Hao (Dissertation)

Type Classes and Instance Chains: A Relational Approach , John Garrett Morris (Dissertation)

Theses/Dissertations from 2012 2012

Using Dataflow Optimization Techniques with a Monadic Intermediate Language , Justin George Bailey (Thesis)

A Survey and Analysis of Solutions to the Oblivious Memory Access Problem , Erin Elizabeth Chapman (Thesis)

A Data-Descriptive Feedback Framework for Data Stream Management Systems , Rafael J. Fernández Moctezuma (Dissertation)

Extending Relativistic Programming to Multiple Writers , Philip William Howard (Dissertation)

The Basic Scheme for the Evaluation of Functional Logic Programs , Arthur Peters (Thesis)

The Link Between Image Segmentation and Image Recognition , Karan Sharma (Thesis)

Relativistic Causal Ordering A Memory Model for Scalable Concurrent Data Structures , Josh Triplett (Dissertation)

Theses/Dissertations from 2011 2011

Conceptual Modeling of Data with Provenance , David William Archer (Dissertation)

Low-latency Estimates for Window-Aggregate Queries over Data Streams , Amit Bhat (Thesis)

Information Processing in Two-Dimensional Cellular Automata , Martin Cenek (Dissertation)

Scalable and Efficient Tasking for Dynamic Sensor Networks , Thanh Xuan Dang (Dissertation)

On the Effect of Topology on Learning and Generalization in Random Automata Networks , Alireza Goudarzi (Thesis)

HOLCF '11: A Definitional Domain Theory for Verifying Functional Programs , Brian Charles Huffman (Dissertation)

A Functional Approach to Memory-Safe Operating Systems , Rebekah Leslie (Dissertation)

Factoring Semiprimes Using PG2N Prime Graph Multiagent Search , Keith Eirik Wilson (Thesis)

High Speed Wireless Networking for 60GHz , Candy Yiu (Dissertation)

Theses/Dissertations from 2010 2010

Extensible Scheduling in a Haskell-based Operating System , Kenneth William Graunke (Thesis)

Addressing Automated Adversaries of Network Applications , Edward Leo Kaiser (Dissertation)

An Automata-Theoretic Approach to Hardware/Software Co-verification , Juncao Li (Dissertation)

Practical Type Inference for the GADT Type System , Chuan-kai Lin (Dissertation)

Scalable event tracking on high-end parallel systems , Kathryn Marie Mohror (Dissertation)

Performance Analysis of Hybrid CPU/GPU Environments , Michael Shawn Smith (Thesis)

Theses/Dissertations from 2009 2009

Computational Techniques for Reducing Spectra of the Giant Planets in Our Solar System , Holly L. Grimes (Thesis)

Programmer Friendly Refactoring Tools , Emerson Murphy-Hill (Dissertation)

A Framework for Superimposed Applications : Techniques to Represent, Access, Transform, and Interchange Bi-level Information , Sudarshan Srivivasa Murthy (Dissertation)

Graphical User Interfaces as Updatable Views , James Felger Terwilliger (Dissertation)

Theses/Dissertations from 2008 2008

Window Queries Over Data Streams , Jin Li (Dissertation)

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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

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

A Hybrid Approach to Procedural Dungeon Generation , Mathias Paul Babin

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Home » Blog » Dissertation » Topics » Computer Science » Computer Science Dissertation Topics (27 Examples) For Research

Computer Science Dissertation Topics (27 Examples) For Research

Mark Jun 12, 2020 Jun 12, 2020 Computer Science No Comments

Computer science is a broad subject, which is creating new research opportunities for students. In this field of study, there are a number of themes and aspects to the study and practically each of them can be used to develop a strong dissertation topic. We have gathered many interesting topics to develop a list of […]

We have gathered many interesting topics to develop a list of computer science dissertation topics. Choosing the right topic from the list of research topics on computer science can help in carrying out research. The project topics on computer science are presented here.

List of Computer science dissertation topics

Can software programs reduce global energy consumption?

How can modern computer applications be supported by operating?

Exploring the best password management applications.

A literature review of the characteristics of a network.

How can data be transformed into dynamic decision making?

Studying the implementation of dart matches analysis.

Differentiating between different modifications in speech manipulator tool.

Exploring the conflicts in software designing and finding ways to detect and manage them proactively.

How to detect cheating in online games based on the behavioural patterns of users?

To study the importance of privacy of electronic records.

A literature review on software development processes and the elimination of risks.

How to design an information system for a multinational company?

Studying the concept of intelligent marketing.

To explore the GUI Test Suites and its automated repair process.

How can the lens of the camera recognise facial expressions and emotions?

To analyse data mining and gene expression analysis in the context of bioinformatics.

Studying the impact of an integrated robotics STEM course for high school students.

To investigate the concept of fuzzy logic controller design for intelligent robots.

A literature review on the real-time embedded systems: present and future.

Security issues, challenges, and solutions related to cloud computing.

Analysing the educational robotics through a comparative study.

Exploring the impact of bioinformatics on medicine and agriculture.

To study cloud computing: a review of different models and concepts.

Investigating the deep neural networks in the context of computational neuroscience.

What is cryptography? A comparative analysis of modern techniques.

Studying the potential of automatic word comparison for historical linguistics.

A literature review on DNA computing-based authentication techniques and its importance.

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The Dissertation

Continuing to Part III

The dissertation should be written for a technically competent reader who is not necessarily familiar with the particular aspects of Computer Science involved. Better grades will arise from clarity and ease of reading, good pictures, clear explanation, minimal jargon and appropriate use of equations. Writing a dissertation requires planning and time. You should allow at least four weeks for the task.

Dissertation PDF files must be

formatted for A4 paper;
Typeset in 12-point font with a minimum of 2 cm margins;
less than 15 megabytes in size;
(ideally) use embedded fonts.

The main body of the dissertation, running from the first page of the introduction until the last page of the conclusions, shall not exceed 40 pages nor exceed 12,000 words in length (including tables and footnotes). Students should ensure the main body of their dissertation (page 3 onwards) as well as any appendices do not contain direct personal identifiers (i.e. their name or their CRSID).

Examiners and Assessors are permitted to judge your work only through study of your dissertation, although they will require your original source code to be available for them to refer to in cases where clarification is needed.

To facilitate the assessment process, the Examiners require the top-level structure of the dissertation to be strictly as follows:

Declaration of originality

Table of contents.

Chapter 1: Introduction
Chapter 2: Preparation
Chapter 3: Implementation
Chapter 4: Evaluation
Chapter 5: Conclusions

Bibliography

Project proposal.

It is not the intention of the Examiners to constrain writers too greatly. Although the layout of the Cover Sheet and the arrangement of the Proforma are tightly specified, the organisation and length of each of the five chapters are allowed to vary considerably from one dissertation to another. Further details are given below.

The cover page

The single cover page contains

Your Name, in the extreme top right-hand corner .
The Title of your Dissertation.
The Examination for which you are a candidate.
Your College and the Year in which you are submitting the Dissertation.

Your project title must be the same as the title approved by your Project Checkers on your project proposal. If you want to change the title you should first discuss this with your supervisor. If your supervisor is in agreement you will need to request a change by contacting the Teaching Administration Manager with a brief explanation for the reasons behind the change ([email protected]). This will be approved by the Teaching Administration Manager and Chair of Examiners.

All dissertations must include an anti-plagiarism declaration immediately before the Proforma. The declaration must have exactly the following syntax:

I, [Name] of [College], being a candidate for Part II of the Computer Science Tripos, hereby declare that this dissertation and the work described in it are my own work, unaided except as may be specified below, and that the dissertation does not contain material that has already been used to any substantial extent for a comparable purpose. [In preparation of this dissertation I did not use text from AI-assisted platforms generating natural language answers to user queries, including but not limited to ChatGPT. / The project required the use of AI-assisted platform [name] in section [number], and such use is acknowledged in the text.] (use either of these sentences as appropriate) [I am content for my dissertation to be made available to the students and staff of the University.]

Signed [signature]

Date [date]

Further guidance relating to the use of AI-assisted tools can be found on the exams guidance web page .

You may either include a scanned copy of your signature or type your full name in place of a handwritten signature.

The University drafted the wording, which is similar to that relating to dissertations in a wide range of subjects; thus the "unaided except as may be specified below" clause merits some explanation:

The clause does not require acknowledgement of the project supervision or informal conversations with peers.
The clause is also intended to cover collaborative projects which are not now permitted in Computer Science. As such this aspect is irrelevant to Computer Science dissertations.
This clause aside, and notwithstanding 1 and 2, candidates are required to draw attention, in the Implementation chapter, to the parts of the work which are not their own, in accordance with the Implementation section below. Other acknowledgements should be given wherever appropriate.

The Department would like past dissertations to be made available for teaching purposes and for your references. These will be accessed on the Computer Science departmental website under Raven password protection. You should include the last sentence of the declaration if you are willing for your dissertation to be accessed for these purposes; otherwise you may remove it. Note: If in the future you would like your dissertation removed from the departmental website, you can request this by contacting the Student Admin office at [email protected].

The proforma page

The single proforma page is a preface that immediately follows the declaration of originality. The proforma page, as well as all subsequent pages of the dissertation should not include direct personal identifiers such as your name or CRSID. The Proforma must be arranged thus:

Your candidate number.
The Title of your Project.
The Examination and Year.
Word-count for the dissertation.
Code line count: Number of lines of code written by the student in the final version of their software.
Project Originator (if this is the student please state 'The candidate').
Project Supervisor.
At most 100 words describing the original aims of the project.
At most 100 words summarising the work completed.
At most 100 words describing any special difficulties that you faced. (In most cases the special difficulties entry will say "None".)

It is quite in order for the Proforma to point out how ambitious the original aims were and how the work completed represents the triumphant consequence of considerable effort against a background of unpredictable disasters. The substantiation of these claims will follow in the rest of the dissertation.

Student Administration will ask students to resubmit any dissertation which does not include the relevant cover page, declaration and proforma. If such a resubmission occurs after the deadline this will result in a late submission penalty.

This should list the contents in some sensible way.

Introduction

The introduction should explain the principal motivation for the project and show how the work fits into the broad area of surrounding computer science and give a brief survey of previous related work. It should generally be unnecessary to quote at length from technical papers or textbooks. If a simple bibliographic reference is insufficient, consign any lengthy quotation to an appendix.

Principally, this chapter should describe the work which was undertaken before code was written, hardware built or theories worked on. It should show how the project proposal was further refined and clarified, so that the implementation stage could go smoothly rather than by trial and error.

Throughout this chapter and indeed the whole dissertation, it is essential to demonstrate that a proper professional approach was employed.

The nature of this chapter will vary greatly from one dissertation to another but, underlining the professional approach, this chapter will very likely include a section headed "Requirements Analysis" and refer to appropriate software engineering techniques used in the dissertation. The chapter will also cite any new programming languages and systems which had to be learnt and will mention complicated theories or algorithms which required understanding.

It is essential to declare the starting point. This states any existing codebase or materials that your project builds on. The text here can commonly be identical to the text in your proposal, but it may enlarge on it or report variations. For instance, the true starting point may have turned out to be different from that declared in the proposal and such discrepancies must be explained.

Implementation

This chapter should describe what was actually produced: the programs which were written, the hardware which was built or the theory which was developed. Any design strategies that looked ahead to the testing stage should be described in order to demonstrate a professional approach was taken.

Descriptions of programs may include fragments of high-level code but large chunks of code are usually best left to appendices or omitted altogether. Analogous advice applies to circuit diagrams or detailed steps in a machine-checked proof.

The implementation chapter should include a section labelled "Repository Overview". The repository overview should be around one page in length and should describe the high-level structure of the source code found in your source code repository. It should describe whether the code was written from scratch or if it built on an existing project or tutorial. Making effective use of powerful tools and pre-existing code is often laudable, and will count to your credit if properly reported. Nevertheless, as in the rest of the dissertation, it is essential to draw attention to the parts of the work which are not your own.

It should not be necessary to give a day-by-day account of the progress of the work but major milestones may sometimes be highlighted with advantage.

This is where Assessors will be looking for signs of success and for evidence of thorough and systematic evaluation. Sample output, tables of timings and photographs of workstation screens, oscilloscope traces or circuit boards may be included. Care should be employed to take a professional approach throughout. For example, a graph that does not indicate confidence intervals will generally leave a professional scientist with a negative impression. As with code, voluminous examples of sample output are usually best left to appendices or omitted altogether.

There are some obvious questions which this chapter will address. How many of the original goals were achieved? Were they proved to have been achieved? Did the program, hardware, or theory really work?

Assessors are well aware that large programs will very likely include some residual bugs. It should always be possible to demonstrate that a program works in simple cases and it is instructive to demonstrate how close it is to working in a really ambitious case.

Conclusions

This chapter is likely to be very short and it may well refer back to the Introduction. It might offer a reflection on the lessons learned and explain how you would have planned the project if starting again with the benefit of hindsight.

It is common, but not mandatory, to have a bibliography. Attention should be given to correct and consistent formatting.

It is common, but not mandatory, to have one or more appendices. Assessors like to see some sample code or example circuit diagrams, and appendices are the sensible places to include such items. Accordingly, software and hardware projects should incorporate appropriate appendices. Note that the 12,000 word limit does not include material in the appendices, but only in extremely unusual circumstances may appendices exceed 10-15 pages. If you feel that such unusual circumstances might apply to you you should ask your Director of Studies and Supervisor to discuss this with the Chairman of Examiners. Appendices should appear between the bibliography and the project proposal.

An index is optional.

A copy of the original project proposal must be included at the very end of the dissertation.

Department of Computer Science and Technology University of Cambridge William Gates Building 15 JJ Thomson Avenue Cambridge CB3 0FD

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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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25 Dissertation & Thesis Topics for Computer Science

Computer science is one of the fastest evolving study areas. A computer science dissertation, therefore, gives you a chance to study anything from sports to medicine and space, among other areas. As all sectors of life embrace technology, the need to explore human interaction with computer hardware and software grows.

When writing a PhD thesis in computer science, the topic is a focal point in your discussion. It will determine the type of books to read, the data to collect, and the overall drafting experience. How do you choose the best computer science thesis topic for your paper? Here are a few insights.

Base the topic on your passion

There are thousands upon thousands of computer science thesis topics you can base your paper on. However, not all will give you a meaningful paper. The best topic is one based on passion. Passion indicates personal interest in a subject. It will help you to produce insightful ideas in your discussion. With passion, you will draft the paper for hours without fatigue.

Evaluate the relevance of your topic

Choose the most relevant thesis topics for computer science. A relevant topic will capture the imagination of a reader. Such a topic is current and helps the readers to solve prevailing challenges in computer science.

Relevant computer science PhD topics are strong and researchable. A grade 5 student discussing a mobile phone or game cannot take the same approach as a Ph.D. student. Relevance means that your paper topic must fit the Ph.D. level of study.

Pick fresh ideas

Fresh computer science master project ideas are interesting to read. They keep away from the old mundane discussions that many other students have explored. With a fresh idea, you give your readers something to look forward to in a paper.

Make the topic interesting

The role of human beings in future computers
Cloud computing and software sales
Self-diagnosing and repairing computers vs the role of future technicians
Cyber security and cloud computing
Automation and job creation or job losses
Artificial intelligence and relegating human beings during interactions with computers
High-performance computers
Computers gadgets and technology for use in international diplomacy, war, and trade
Human perception and interaction with VR gadgets
Machine neuron networks
Computer gadgets and war minerals
Medicine, biotechnology, and computer science
Covid-19 vaccine development and the place of technology
Face recognition technology in fighting crime
Computer usage in the education sector
Reducing screen-time while embracing computers in class
Data security and the advanced features on mobile phones
Global companies and data security
Wireless connectivity and permissions
5G technology and future possibilities
Password system and human memory
Biometric systems and data security
E-health systems and data privacy concerns
Authenticators vs passwords
Facial and emotional identification

The best masters project ideas computer science are specific. The topic should provide a boundary to guide the reader on the expectations to have about a paper. For instance, if you are studying technology in medicine, you can choose a specific area like surgery or diagnostics. A reader looking for any other information will not pin his hope on your paper. Such a specific topic ensures that your paper meets the expectations of a reader. Choose a good topic for your paper and you will have the most enjoyable writing experience.

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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

We Can Help You with Computer Science Topics, Essays, Thesis, and Research Papers

We hope that this list of computer science topics helps you out of your sticky situation. We do offer other topics in different subjects. Additionally, we also offer professional writing services tailor-made for you.

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.

Don’t waste any more time; get in touch with us today and get your paper done excellently.

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141 Computer Science Dissertation Ideas – Take An Original Approach!

Computer science is not a field anyone would approach with utter carelessness. It is one of the fields that makes college and university students go insane. Some end up dropping halfway because of the pressure that comes with such assignments. However, there is a professional way out that offers you the best solutions you can ever think of in your academic endeavors.

Impress your professor with our brilliant computing ideas.

How To Develop Computing Dissertation Ideas

A research paper in computer science deals with concepts related to information technology by professionals, scholars, and scientists. When writing your computer science research paper, consider the following:

Choose a top-notch topic: Your topic plays a vital role in your paper. Therefore, you have to choose a relevant topic, specific, and one that offers a solution. It should also give the reader a general picture of what to expect in the content paragraphs. Have evaluative thinking: When deciding what to write, think like your instructor will evaluate your paper. What key points will he/she look out for in your article? What will motivate him/her to be impressed with your report? Having such in mind will help you create a top-notch paper. Consult different sources: To achieve the best results, you should have a lot of information at hand. The best way to accomplish this would be through consulting both online and offline sources to give you an idea of what to write. Since computer science is an evolving field, ensure that the seeds you consult are up to date. Avoid jargon: Computer science may have various jargon that is not compatible with every reader. As such, you should strive to break down the complex computer science terms into relatable and reader-oriented words.

Using these tricks, you can be sure of a tip-top computer science paper. There are various ways of developing computer science topics such as:

Journals and articles on computer science
Online sources on computer science
Your class lecture notes

The secret of having professional computer science topics is to be as simple as possible. Many students tend to look for complex issues which frustrate them in the end.

Look at these computer science ideas for your inspiration.

The Best Computer Science Dissertation Ideas

Cloud computing challenges and solutions in line with security
Are software programs able to reduce global energy consumption?
Ways in which the integrated robotics STEM course has affected high school students
A review on the implementation of dart matches
Ways to detect and manage conflicts in software designing
How the behavioral pattern of users can help curb cheating in online games
Ways in which modern computer applications can be supported by operating
The study of DNA computing-based authentication skills and their importance
A review on the concept of intelligent marketing
Exploring different models and concepts related to cloud computing
Ways that camera lens detect facial expressions and emotions
Transformation of data into dynamic decision making
The present and future study on the real-time embedded system
A review on cryptography about modern techniques
Ways of designing an information system for a multinational company
A comparative survey of the educational robotics
Exploring the benefits of piracy of electronic records
A study on the characteristics of a network
The automated repair process of the GUI Test suites and their study
How bioinformatics has affected the medicine and agricultural sector

Top-Notch Computing Dissertation Ideas

Advantages of mobile messaging system for higher education
The impact of social network in present day
How can IT improve the value of inter-organizational knowledge?
Advantages and disadvantages of Biometrical technologies
How artificial intelligence has impacted advertising and marketing
Distributed systems and their testing on a system level
A review of a cloud-based IS for the grain storage company
Ways on how to design a secure component-based networking monitoring tool from struts and hibernates
A study on network security through a programmatic approach

Computer Science Dissertation Projects For High Grades

Ways of preventing unsuccessful implementation of software development
Challenges related to development of information systems and database design
How Bio-informatics improve healthcare services
A study on strategic and methodological approaches for the development of ICT systems
Ways of designing and implementing a distributed file-sharing system used for supporting content mobility
How to conduct a test for the performance analysis of over Windows Operating Ethernet LANs
Ways of improving the security of smartcard network transmission
The Impact signal strength has on WI-FI link throughput using propagated measurements
A review on the performance study of VOIP over wireless and Ethernet LAN
A survey of the issues of coordinated transmission techniques in the future generation 5G wireless networks
A review on scalable router placement in software-defined networks
Ways to monitor a young person’s activities all over social media and develop patterns
How artificial intelligence improves human-computer interaction on personal computers
How a camera helps in tracking over-speeding
Ways of improving human-computer interaction by using artificial intelligence system on mobile devices
How to manage and track traffic fines using extensive data analysis

Computer Science Dissertation Topics To Impress Your Professor

A study on building information system for e-learning in educational institutes
Exploring various models of e-marking services through a computer, networks, and the internet
The impact of internet-based services on e-marketing
The study of e-marketing challenges and solutions
Research on how to implement a new integrated information system in the library
How the full-text databases have impacted the search engine services
How shopping cart users have been affected by full-text databases
Ways in which the internet and cyberinfrastructure has involved jobs and income
How marketing users have been affected by the internet and cyberinfrastructure
A review of collaborative social network tools for the gathering and classification of information from the society
What are the government policies towards the adoption and diffusion of ICT?
The effect of e-publishing on the future of libraries
How has the web affected library users?
A study on changing of web space requirements
How to change management in a web environment

Expert Computer Science Research Topics

A review on designing an effective intrusion detection system for 4G networks
Challenges and opportunities brought by migrating to web-based information services.
Challenges and future directions on e-recruitment standards
How to develop an exercise-workout tracking app on Android/IOS
Study on how to build web systems for the intelligent cinema tickets booking system
Java programs for applied financial systems
Ways to detect network traffic anomaly with SDN
Transferring data through P2P and WI-FI networks: how to do it securely?
Database technologies in managing networking data
Study of fault recovery and redundancy in real-time WNS
4G WNS: full review of redundancy and fault recovery
Characteristics protocol and anonymous routing: main principles

Calculated Computer Science Topics

How the development of IP networks relate to the environment
How dynamic proxies helps in supporting RMI in a mobile environment
The role of the computer in the making of face masks
How computer has aided in the making of modern ventilators
Ways in which the computer has helped spread the news of new covid 19 cases around the world.
How computer study has helped in creating new software in the modern world
Careers in web development through the study of computer science
How to gain basic programming skills and software development when study computer science.
Computer science becomes challenging when the student doesn’t get enough materials.
Advanced skills in programming, software development, and basic computing skills
How learning has become simple with the introduction of online classes
Ways of studying and graduating with first-class honors in computer science.
Online study of computer science has helped many student graduates while working during their free time.
How the application of computer science study has helped in the growth of online business
How churches are conducting online services around the world under lockdown
Ways in which computer scientist help in the growth of online businesses

Forensic Computing Dissertation Ideas

The computer has helped in the passing of information from one company to another.
Computer scientists are bridging the gap between businesses and online customers.
Online voting has become easy and straightforward through the development of new computer software.
How online libraries have helped poor students access books
Helping poor communities access medical services through computer software
How Africa is changing through the study of computer science
A day in the hands of a computer scientist
Why a computing job is so demanding and time-consuming
How computers have replaced the use of letters and communication in general.
Solving problems affecting online businesses through the study of computer science
How mathematics lovers find it easy to study computer science
The role of computers in the operation of medical equipment and machines
Computer developer’s role in the control of the movement of goods around the world.
How computer scientist is solving modern challenges with new software
Dealing with online learning problems brought by the fast-moving world

Professional Computing Dissertation Project Ideas

How communities are helping in the growth of computer scientists
Spreading of crucial information about computer science around the world
Common mistakes students make when learning about computing
Why good knowledge in mathematics helps when studying computers
Must have tools when preparing to study computer science
How computer engineers are coming up with fast working computers
How computers are helping in the increase of cyber crimes
The role of computer engineers in curbing cybercrimes.
Key roles computer scientists play in the growth of Economy
Factors affecting the growth of online businesses around the world
How computer science has replaced face to face meeting with online meetings
Computer study has promoted the increase of web pages around the world
Whys of managing a company without stepping into your office using a computer
Managing and running businesses using your laptop at home
How computer engineers are coming up with ways of dealing with slow computers
The study of computer science and its application requires patients and commitment
Ways in which computer engineers have promoted the security of documents in computers
How the invention of new computers has increased the unemployment rate around the world.
Computer study has negatively affected the spread of accurate information from one person to another.
How computer study has helped in the growth of new modern cities around the world
Ways in which computers have affected the management of sports
Knowledge of the computer has increased due to the invention of fast and straightforward to use computers
The role of computer science in water filtration

A+ Computer Science Topics

Ways in which engineers are coming up with ways of linking phones with computers
How companies are losing money through computers hacking
Ways in which computers are slowing businesses around the world
Use of computer software in doing business
How cloud computing is transforming the world
Imparts of production of fast working computers in the world
The roles of computers in the day to day running of online businesses
Ways of using computers to promote trade between countries
Role of computer in helping curb insecurities in major cities
How computers are assisting companies in operating in countries with different time zones
The parts of a computer in the building and construction of modern houses
Ways in which computer study is promoting the growth of industries
Why there are few computer science lecturers
How computer science is helping in forensics
Computer science and book publishing.

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Computer Science Dissertation Topics – Expert Advice

Published by Alvin Nicolas at December 22nd, 2022 , Revised On February 2, 2024

Writing a dissertation or a thesis paper can turn out to be a forgettable experience for many computer science students in UK universities. Before students can start working on their dissertation project, they must choose an appropriate computer science dissertation topic and have it approved by their supervisor.

It can actually be quite tricky and challenging to find a focused and unique topic for a thesis or dissertation in computer science, as it is one of the most diversified disciplines chosen by students. In this technological age, we see computer science at the forefront of technological advancements in all areas of life.

The precursor of the change to how we function as a society in recent times is technology. Without technology, our lives would be incomplete today. This progress has its roots in computer science. Students must explore the latest computer science technologies as part of their dissertation or thesis project, as the future depends on them.

How to Find a Good Computer Science Dissertation Topic?

Choosing a topic is the first and most crucial step in a dissertation writing process . It depends a lot on your interests and skills. Before getting started, identify your strengths in computer science and the areas you would like to explore in your studies. The following recommendations can help you develop a preliminary idea before finalising a topic.

Selecting a reputable academic supervisor should be your number one priority. Working with a professor whose interests align with your topic is essential; otherwise, you will not benefit from the dissertation writing process.
Do not limit your search for a dissertation topic to work that has already been defended. Ask your supervisor to list the most compelling, ongoing challenges in computer science. Your supervisors have in-depth knowledge and are aware of research directions being pursued in their respective scientific areas of interest. They may have a brilliant dissertation proposal and help implement it.
Remember that computer science is used in numerous fields today. It can be used in physics, medicine, education and entertainment. You can highlight the theoretical aspect of a particular problem or discuss how you would use a specific programme in practice.

You must choose your dissertation topic carefully if you want your computer science dissertation project to be approved. After investing months of struggle in a dissertation, no one can afford to make a mistake and have the work rejected.

The key to professional computer science topics is to keep them as simple as possible. Many students tend to look for complex problems, which eventually frustrates them. You can also read about our dissertation writing service to see if EssaysUK experts can help you with your project in any way.

Dissertation Links

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Here is a list that can help you complete your computer science dissertation for both your undergraduate and master’s degrees:

List of Topics for Undergraduate and Master’s degree

Can software applications help to reduce global energy consumption?
How is the impact of traffic accidents on a road network predicted? Discuss it by studying and using actual traffic data.
The integrated robotics MEM course has impacted high school students in several ways.
Exploring and emphasising authentication skills based on DNA computing.
Exploring how JAVA programs were created for the applicable financial system and the benefits they provide for efficient financial management.
Exploring different cloud computing methods and concepts.
A study on computer uses in universities and classrooms in wealthy countries.
A research project on the strategic and methodological framework for developing ICT systems.
How can necessary objects be found? An investigation of unsupervised detector matching techniques in use today.
The effect of signal intensity on the throughput of WI-FI connections is investigated using propagation measurements.
Can computers recognise faces? Evaluate the performance of support vector machines for computer vision.
An overview of the issues with coordinated transmission methods in future 5G mobile networks.
Investigate how e-marketing services are used and how this has helped retail businesses.
Methods for tracking a young person’s social media activity and identifying trends.
Observe individuals’ online behaviour to see how it has shaped their personality.
How human-computer interaction on personal computers is enhanced by artificial intelligence
Explore how cyberinfrastructure affects a retailer’s marketing goals.
To see ways of using mobile artificial intelligence systems to improve human-computer interaction.
Exploring the use of computers, networks and the Internet to explore different models for e-marking services.
An investigation of cooperative social network technologies for obtaining and organising information from society.

Software and Programming Dissertation Topics

Using software frameworks such as the Microsoft.NET framework to develop a system for task assignment and room booking
The application of the optimal method for calculating association rules in a given context and its evaluation
The application and evaluation of the best algorithm for clustering
Implementing and evaluating the best approach for creating the best and near-best classification trees.
Implementation and evaluation of heuristic algorithms for computing association rules
Implementation and evaluation of the Custer-generating heuristic algorithm
Implementation and assessment of heuristic algorithms for generating ideal and near-ideal classification trees
A paradigm for programming databases without SQL or table knowledge, using various techniques to construct intelligent database interfaces.
Multiple passes and constant control variables for fault-tolerant routing of interconnection networks.
Identify the framework for web services security analysis, design and implementation.
Analysis of the hardware based on residual number systems for high-speed computations.
Use of efficient algorithms for one-way hashing functions and evaluation of these algorithms.
Evaluation of embedded software systems using different approaches.
Discuss the methods for designing a dynamic proxy-based architecture for distributed Java objects in a mobile environment.
Study the relationship between the serialisation of mobile code and modular data.

Security and Network Dissertation Topics

How can relay attacks be stopped and the security of smart card network signals be increased?
How can a robust intrusion detection system be created for 4G networks?
Think about using intrusion detection technologies to make sense of data across different gateways.
How can I design a secure runtime programming environment to investigate the operations of malicious network worms and botnets?
What are strategic and methodological methods used in developing ICT systems?
How can a secure, scalable and component-based network be built?
An evaluation framework for secure routing-structured peer-to-peer (overlay) networks.
What challenges are facing the coordinated transmission techniques of the following 5G mobile networks?
Analysethe Studies on the efficiency of VOIP over wireless LANs and Ethernet.
What influence does signal strength have on the throughput of a Wi-Fi connection based on propagation measurements?
Use of software-defined networks to detect unusual network traffic.
How can data flow over Wi-Fi and P2P networks be secured?
How is data management possible in networks with database technologies?
How to create an Android/IOS exercise-tracking application?
Study of redundancy and fault recovery in real-time WNS.

Forensic Computer Science Dissertation Topics

How have computers facilitated the transfer of information between businesses?
Analyse how businesses and Internet users are becoming more integrated thanks to computer scientists.
Online voting is now simple and easy, thanks to the development of modern computer software. Discuss
Using computer technologies, discuss how to help underserved communities access healthcare.
How have computers replaced letters and other forms of communication?
The function of computers in the functioning of machines and medical equipment.
The importance of computer developers in regulating the global trade in products.
How are computer scientists using new tools to solve current problems?
Why is it essential to understand mathematics well when learning computers?
To investigate the application of the Genetic Algorithm in the business world.
An investigation of quantum computing methods and their advantages and disadvantages.
An investigation of the literature to explore the relationship between genotype and phenotype.
An investigation into designing a fuzzy logic controller for intelligent robots.
Investigation and comparison of the best password management programs.
Why is it so difficult and time-consuming to work on the computer?

Information Technology Dissertation Topics

The impact of full-text databases on customers’ use of shopping baskets.
Impact of cyber-infrastructure and the Internet on employment and income in the UK.
The Internet and cyberinfrastructure impact marketing and marketing users in the UK.
Relation between Information gathering and impact on information seeking.
Integration of web and multimedia and measuring the impact of programs on language use.
Impact of Internet-based products, services and technologies on use, customer service and e-marketing.
Several electronic marketing service models use computers, networks and the Internet.
Challenges in building information systems for large health organisations such as the NHS UK.
Issues and future directions concerning electronic recruitment standards.
The advantages and disadvantages of moving to web-based information services.
An analysis of collaborative social networking technologies for collecting and classifying data from children, young people, adults and older people.
ICT adoption and diffusion by the UK government, including e-government services and high-speed internet access for citizens and customers.

Professional Computer Science Dissertation Topics

Evaluate the possibilities of cloud computing for e-commerce companies.
Investigate the idea of developing a fuzzy logic controller for intelligent robots.
Describe cryptography. A theoretical evaluation of the idea and its function.
Global factors influencing the expansion of online businesses.
How have face-to-face meetings been replaced by online sessions thanks to computing?
How is society shifting away from face-to-face interaction to computer engagement?
Explore the process of data management and storage.
Explore data warehousing applications in the financial sector through a case study.
To explore the idea of numerous devices being connected.
Explore the application of IoT in the context of agriculture in poor countries.
The efforts of computer developers to increase the security of documents stored on computers.
How has the global unemployment rate increased due to the development of new computers?
How have computer studies made spreading reliable information from one person to another more difficult?
How do computers help companies to work in countries with different time zones?
An evaluation of the usefulness of support vector machines for computer vision.
Examine the many methods and formulas for indexing and parsing multimedia databases.
Intelligent marketing involves the incorporation of artificial intelligence concepts and techniques into the advertising and marketing process.
Detection of cheating in online games based on user behaviour patterns.
Explore how homomorphism encryption is used for key sharing and managing essential data.
Identifying the requirements of an enterprise content management system for a software development firm.

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These are some of the excellent computer science dissertation topics that students can use for their projects. You can customise these topics according to your own preferences or get help from our experts to receive custom computer science thesis topics and ideas directly at your email address.

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List down the top 5 computer science dissertation topics.

1. “Advancements in artificial intelligence for automated cybersecurity defenses.” 2. “Exploring the potential of quantum computing in solving complex optimization problems.” 3. “Developing efficient algorithms for large-scale graph data analysis in social networks.” 4. “Investigating the impact of blockchain technology on secure and decentralized data storage.” 5. “Enhancing privacy in online social networks through novel encryption and access control mechanisms.”

Thesis and Research Topics in Computer Science

Completing a masters Thesis in computer science is the most challenging task faced by research scholars studying in universities all across the world. As computer science is one of the most vast fields opted by research scholars so finding a new thesis topic in computer science becomes more difficult. With each passing day, new and innovative developments are coming out in this era of mechanization. These developments tend to make human life much easier and better. Technology is the forerunner of this new change. Today our life is incomplete without this technology. Cell phones, laptops and all that have become an integral part of our life. Computer Science is the seed to this technical development. There are a number of good topics in computer science for project, thesis, and research for M.Tech and Ph.D. students.

In the field of academics, we need to get rid of obsolete ideas and focus on new innovative topics which are fast spreading their arms among the vast global audience. Computer Science students both in bachelors and in masters are studying the same topics and subjects from the past few years. Students don’t even have knowledge about new masters research topics. For project and thesis work also they are relying on outdated topics. Projects like school management system, library management system etc. are now out of date. Students should shift their focus to latest technologies which are highly in demand these days and future depend upon these. Here is the list of latest topics in Computer Science that you can choose and work for your project work or thesis and research:

List of few latest thesis topics in computer science is below:

Thesis topics in data mining
Thesis topics in machine learning
Thesis topics in digital image processing
Latest thesis topics in Internet of things (IOT)
Research topics in Artificial Intelligence
Networking can be chosen as a thesis topic in computer science
Trending thesis topics in cloud computing
Data aggregation as a thesis topics in Big Data
Research topics in Software Engineering

Data Warehousing

Data Warehousing is the process of analyzing data for business purposes. Data warehouse store integrated data from multiple sources at a single place which can later be retrieved for making reports. The data warehouse in simple terms is a type of database different and kept isolated from organization’s run-time database. The data in the warehouse is historical data which is helpful in understanding business goals and make decisions for future prospects. It is a relatively new concept and have high growth in future. Data Warehouse provides Online Analytical Processing(OLAP) tools for the systematic and effective study of data in a multidimensional view. Data Warehouse finds its application in the following areas:

Financial Sector
Banking Sector
Retail Services
Consumer goods
Manufacturing

So start working on it if you have knowledge of database and data modeling.

INTERNET OF THINGS(IOT)

Internet of Things(IoT) is a concept of interconnection of various devices, a vehicle to the internet. IOT make use of actuators and sensors for transferring data to and from the devices. This technology is developed for better efficiency and accuracy apart from minimizing human interaction with the devices. The example for this is home heating in some countries when the temperature drops done through motion sensors which automatically detect the weather conditions. Another example for this is the traffic lights which changes its colors depending upon the traffic. Following are the application areas of Internet of Things(IoT):

Home Automation
Agriculture
Transportation
Environment

BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN IOT :-

The secure and energy efficient data routing in the IOT based networks
The secure channel establishment algorithm for the isolation of misdirection attack in the IOT
The clock synchronization of IOT devices of energy efficient data communication in IOT
The adaptive learning scheme to increase fault tolerance of IOT
Mobility aware energy efficient routing protocol for Internet of Things
To propose energy efficient multicasting routing protocol for Internet of Things
The novel scheme to maintain quality of service in internet of Things
Link reliable and trust aware RPL routing protocol for Internet of Things
The energy efficient cluster based routing in Internet of Things
Optimizing Multipath Routing With Guaranteed Fault Tolerance in Internet of Things

Many people are not aware of this concept so you can choose for your project work and learn something new.

Big Data is a term to denote the large volume of data which is complex to handle. The data may be structured or unstructured. Structured data is an organized data while unstructured data is an unorganized data. Big data can be examined for the intuition that can give way to better decisions and schematic business moves. The definition of big data is termed in terms of three Vs. These vs are:

Volume: Volume defines large volume of data from different sources
Velocity: It refers to the speed with which the data is generated
Variety: It refers to the varied amount of data both structured and unstructured.

Application areas:

BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN BIG DATA :-

Privacy preserving big data publishing: a scalable k-anonymization approach using MapReduce.
Nearest Neighbour Classification for High-Speed Big Data Streams Using Spark.
Efficient and Rapid Machine Learning Algorithms for Big Data and Dynamic Varying Systems.
Disease Prediction by Machine Learning Over Big Data From Healthcare Communities.
A Parallel Multi-classification Algorithm for Big Data Using an Extreme Learning Machine.

Thus you can prepare your project report or thesis report on this.

Cloud Computing

Cloud Computing is a comparatively new technology. It is an internet-based service that creates a shared pool of resources for consumers. There are three service models of cloud computing namely:

Software as a Service(SaaS)
Platform as a Service(PaaS)
Infrastructure as a Service(IaaS)

Characteristics of cloud computing are:

On-demand self-service
Broad network access
Shared pool of resources
Scalability
Measured service

Below is the list of few latest and trending research topics in Cloud Computing :-

To isolate the virtual side channel attack in cloud computing
Enhancement in homomorphic encryption for key management and key sharing
To overcome load balancing problem using weight based scheme in cloud computing
To apply watermarking technique in cloud computing to enhance cloud data security
To propose improvement green cloud computing to reduce fault in the network
To apply stenography technique in cloud computing to enhance cloud data security
To detect and isolate Zombie attack in cloud computing

The common examples of cloud computing include icloud from Apple, Google-based Services like Google Drive and many more. The field is very demanding and is growing day by day. You can focus on it if you have interest in innovation.

Semantic Web

Semantic Web is also referred to as Web 3.0 and is the next big thing in the field of communication. It is standardized by World Wide Web Consortium(W3C) to promote common data formats and exchange protocols over the web. It is machine-readable information based and is built on XML technology. It is an extension to Web 2.0. In the semantic web, the information is well defined to enable better cooperation between the computers and the people. In the semantic web, the data is interlinked for better understanding. It is different from traditional data sharing technologies.

It can be a good topic for your thesis or project.

MANET stands for mobile ad hoc network. It is an infrastructure-less network with mobile devices connected wirelessly and is self-configuring. It can change locations independently and can link to other devices through a wireless connection. Following are the various types of MANETS :

Vehicular ad hoc network(VANET)
Smartphone ad-hoc network(SPANET)
Internet-based mobile ad hoc network(iMANET)

You can use various simulation tools to study the functionality and working of MANET like OPNET, NS2 , NETSIM, NS3 etc.

In MANET there is no need of central hub to receive and send messages. Instead, the nodes directly send packets to each other.

MANET finds its applications in the following areas:

Environment sensors
Vehicular ad hoc communication
Road Safety

BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN MANET :-

Evaluate and propose scheme for the link recovery in mobile ad hoc networks
To propose hybrid technique for path establishment using bio-inspired techniques in MANET’s
To propose secure scheme for the isolation of black hole attack in mobile ad hoc networks
To propose trust based mechanism for the isolation of wormhole attack in mobile ad hoc networks
The novel approach for the congestion avoidance in mobile ad hoc networks
To propose scheme for the detection of selective forwarding attack in mobile ad hoc networks
To propose localization scheme which reduce faults in mobile ad hoc network
The energy efficient scheme for multicasting routing in wireless ad hoc network
The scheme for secure localization aided routing in wireless ad hoc networks
The cross-layer scheme for opportunistic routing in mobile ad hoc networks

Just go for it if you have interest in the field of networking and make a project on it.

Machine Learning

It is also a relatively new concept in the field of computer science and is a technique of guiding computers to act in a certain way without programming. It makes use of certain complex algorithms to receive an input and predict an output for the same. There are three types of learning;

Supervised learning
Unsupervised learning
Reinforcement learning

Machine Learning is closely related to statistics. If you are good at statistics then you should opt this topic.

Data Mining

Data Mining is the process of identifying and establishing a relationship between large datasets for finding a solution to a problem through analysis of data. There are various tools and techniques in Data Mining which gives enterprises and organizations the ability to predict futuristic trends. Data Mining finds its application in various areas of research, statistics, genetics, and marketing. Following are the main techniques used in the process of Data Mining:

Decision Trees
Genetic Algorithm
Induction method
Artificial Neural Network
Association

BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN DATA MINING :-

Performance enhancement of DBSCAN density based clustering algorithm in data mining
The classification scheme for sentiment analysis of twitter data
To increase accuracy of min-max k-mean clustering in Data mining
To evaluate and improve apriori algorithm to reduce execution time for association rule generation
The classification scheme for credit card fraud detection in Data mining
To propose novel technique for the crime rate prediction in Data Mining
To evaluate and propose heart disease prediction scheme in Data Mining
Software defect prediction analysis using machine learning algorithms
A new data clustering approach for data mining in large databases
The diabetes prediction technique for Data mining using classification
Novel Algorithm for the network traffic classification in Data Mining

Advantages of Data Mining

Data Mining helps marketing and retail enterprises to study customer behavior.
Organizations into banking and finance business can get information about customer’s historical data and financial activities.
Data Mining help manufacturing units to detect faults in operational parameters.
Data Mining also helps various governmental agencies to track record of financial activities to curb on criminal activities.

Disadvantages of Data Mining

Privacy Issues
Security Issues
Information extracted from data mining can be misused
Artificial Intelligence

Artificial Intelligence is the intelligence shown by machines and it deals with the study and creation of intelligent systems that can think and act like human beings. In Artificial Intelligence , intelligent agents are studied that can perceive its environment and take actions according to its surrounding environment.

Goals of Artificial Intelligence

Following are the main goals of Artificial Intelligence:

Creation of expert systems
Implementation of human intelligence in machines
Problem-solving through reasoning

Application of Artificial Intelligence

Following are the main applications of Artificial Intelligence:

Expert Systems
Natural Language Processing
Artificial Neural Networks
Fuzzy Logic Systems

Strong AI – It is a type of artificial intelligence system with human thinking capabilities and can find a solution to an unfamiliar task.

Weak AI – It is a type of artificial intelligence system specifically designed for a particular task. Apple’s Siri is an example of Weak AI.

Turing Test is used to check whether a system is intelligent or not. Machine Learning is a part of Artificial Intelligence. Following are the types of agents in Artificial Intelligence systems:

Model-Based Reflex Agents
Goal-Based Agents
Utility-Based Agents
Simple Reflex Agents

Natural Language Processing – It is a method to communicate with the intelligent systems using human language. It is required to make intelligent systems work according to your instructions. There are two processes under Natural Language Processing – Natural Language Understanding, Natural Language Generation.

Natural Language Understanding involves creating useful representations from the natural language. Natural Language Generation involves steps like Lexical Analysis, Syntactic Analysis, Semantic Analysis, Integration and Pragmatic Analysis to generate meaningful information.

Image Processing

Image Processing is another field in Computer Science and a popular topic for a thesis in Computer Science. There are two types of image processing – Analog and Digital Image Processing. Digital Image Processing is the process of performing operations on digital images using computer-based algorithms to alter its features for enhancement or for other effects. Through Image Processing, essential information can be extracted from digital images. It is an important area of research in computer science. The techniques involved in image processing include transformation, classification, pattern recognition, filtering, image restoration and various other processes and techniques.

Main purpose of Image Processing

Following are the main purposes of image processing :

Visualization
Image Restoration
Image Retrieval
Pattern Measurement
Image Recognition

Applications of Image Processing

Following are the main applications of Image Processing:

UV Imaging, Gamma Ray Imaging and CT scan in medical field
Transmission and encoding
Robot Vision
Color Processing
Pattern Recognition
Video Processing

BELOW IS THE LIST OF FEW LATEST AND TRENDING RESEARCH TOPICS IN IMAGE PROCESSING :-

To propose classification technique for plant disease detection in image processing
The hybrid bio-inspired scheme for edge detection in image processing
The HMM classification scheme for the cancer detection in image processing
To propose efficient scheme for digital watermarking of images in image processing
The propose block wise image compression scheme in image processing
To propose and evaluate filter based on internal and external features of an image for image de noising
To improve local mean filtering scheme for de noising of MRI images
To propose image encryption base d on textural feature analysis and chaos method
The classification scheme for the face spoof detection in image processing
The automated scheme for the number plate detection in image processing

Bioinformatics

Bioinformatics is a field that uses various computational methods and software tools to analyze the biological data. In simple words, bioinformatics is the field that uses computer programming for biological studies. It is the current topic of research in computer science and is also a good topic of choice for the thesis. This field is a combination of computer science, biology, statistics, and mathematics. It uses image and signal processing techniques to extract useful information from a large amount of data. Following are the main applications of bioinformatics:

It helps in observing mutations in the field of genetics
It plays an important role in text mining and organization of biological data
It helps to study the various aspects of genes like protein expression and regulation
Genetic data can be compared using bioinformatics which will help in understanding molecular biology
Simulation and modeling of DNA, RNA, and proteins can be done using bioinformatics tools

Quantum Computing

Quantum Computing is a computing technique in which computers known as quantum computers use the laws of quantum mechanics for processing information. Quantum Computers are different from digital electronic computers in the sense that these computers use quantum bits known as qubits for processing. A lot of experiments are being conducted to build a powerful quantum computer. Once developed, these computers will be able to solve complex computational problems which cannot be solved by classical computers. Quantum is the current and the latest topic for research and thesis in computer science.

Quantum Computers work on quantum algorithms like Simon’s algorithm to solve problems. Quantum Computing finds its application in the following areas:

The list is incomplete as there are a number of topics to choose from. But these are the trending fields these days. Whether you have any presentation, thesis project or a seminar you can choose any topic from these and prepare a good report.

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Computer science is the study of computers and computational systems, including software and hardware design, algorithm development, and problem-solving using computational methods. The digital shift in businesses highlights computer science's significance as a trending academic subject. Thus, students must look for new computer science dissertation topics for their dissertation modules.

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Dissertations / Theses on the topic 'Computer science in Education'

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Consult the top 50 dissertations / theses for your research on the topic 'Computer science in Education.'

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Bewley, Samantha. "High School Computer Science Education." Thesis, Villanova University, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13426311.

One of the challenges in the field of computer science is teaching the subject at the high school level. Thirteen computer science teachers, one technology teacher and one department chair for technology were interviewed to determine how they thought computer science education could be improved at the high school level. The qualitative research addressed curriculum, professional development, educational computer science standards and frameworks, technology, and pedagogy. Institutional Review Board approval was obtained for the research. Nvivo was used to analyze the interviews. When the results were compiled, many teachers were concerned that there were low numbers of students interested in computer science. Having low numbers or students enrolled in computer science classes contribute to low numbers of computer science teachers. Different way to address these problems are proposed.

Ryu, Mike Dongyub. "Improving Introductory Computer Science Education with DRaCO." DigitalCommons@CalPoly, 2018. https://digitalcommons.calpoly.edu/theses/1943.

Peterson, Cynthia Lynn. "Using computer technology to enhance science education." CSUSB ScholarWorks, 2002. https://scholarworks.lib.csusb.edu/etd-project/2109.

Hickey, Peter J. "A microcomputer network for computer science education." Thesis, University of Ottawa (Canada), 1986. http://hdl.handle.net/10393/5023.

Gibson, Benjamin Ian. "Educational Games for Teaching Computer Science." Thesis, University of Canterbury. Computer Science and Software Engineering, 2013. http://hdl.handle.net/10092/9239.

English, John. "A building blocks approach to computer science education." Thesis, University of Brighton, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.485950.

Enström, Emma. "On difficult topics in theoretical computer science education." Doctoral thesis, KTH, Teoretisk datalogi, TCS, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-152357.

QC 20140929

Aldakheel, Eman A. "A Cloud Computing Framework for Computer Science Education." Bowling Green State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1322873621.

Prottsman, Christie Lee Lili. "Computational Thinking and Women in Computer Science." Thesis, University of Oregon, 2011. http://hdl.handle.net/1794/11485.

Mitchell, Carmen L. (Carmen Lois). "The Contributions of Grace Murray Hopper to Computer Science and Computer Education." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc278692/.

Henderson, Craig Allen 1972. "RobotWorld : a simulation environment for introductory computer science education." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80075.

Hutchins-Korte, Laura. "Learning by game-building in theoretical computer science education." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/3162.

Mork, Kirsten L. "Evaluating Creative Choice in K-12 Computer Science Curriculum." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2038.

Anandan, Senthil Kumar. "Animation tool kit for computer science education on the Internet." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0004/MQ45314.pdf.

Symeonidis, Pavlos. "Automated assessment of Java programming coursework for computer science education." Thesis, University of Nottingham, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.437093.

Schroeder, Leah M. "The value of computer-assisted instruction in secondary science education." CSUSB ScholarWorks, 1986. https://scholarworks.lib.csusb.edu/etd-project/172.

Liebe, Christine Lynn. "An Examination of Abstraction in K-12 Computer Science Education." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/6728.

Nadarajah, Kumaravel. "Computers in science teaching: a reality or dream; The role of computers in effective science education: a case of using a computer to teach colour mixing; Career oriented science education for the next millennium." Thesis, Rhodes University, 2000. http://hdl.handle.net/10962/d1003341.

Peterson, Sarah Budinger. "Factors relating to the acquisition of computer literacy and computer science skills in California high schools." Scholarly Commons, 1986. https://scholarlycommons.pacific.edu/uop_etds/3071.

Lowhorn, Greg L., and Anthony Pittarese. "Business Literacy for the Computer Science Professional." Digital Commons @ East Tennessee State University, 2008. https://dc.etsu.edu/etsu-works/3011.

Stejskal, Ryan. "Test-Driven Learning in High School Computer Science." Thesis, University of Nebraska at Omaha, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1554641.

Test-driven development is a style of software development that emphasizes writing tests first and running them frequently with the aid of automated testing tools. This development style is widely used in the software development industry to improve the rate of development while reducing software defects. Some computer science educators are adopting the test-driven development approach to help improve student understanding and performance on programming projects. Several studies have examined the benefits of teaching test-driven programming techniques to undergraduate student programmers, with generally positive results. However, the usage of test-driven learning at the high school level has not been studied to the same extent. This thesis investigates the use of test-driven learning in high school computer science classes and whether test-driven learning provides benefits for high school as well as college students.

Alharbi, Eman. "Characterize the Difficulties that International Computer Science Students Face." Thesis, University of Colorado at Colorado Springs, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10102300.

International Computer Science students, who form the majority of students in Engineering colleges in the U.S (Anderson, 2013), face a lot of difficulties and barriers that are unknown and unexpressed. Hiding these struggles may affect the quality of their education, and will repeat the struggles over and over with the coming students. We conducted a qualitative study to discover the barriers that international Computer Science students have and their special needs. The data was collected by interviewing international Computer Science students and some of their instructors in the University of Colorado at Colorado Springs (UCCS). The study found that international Computer Science students have English barriers evaluated on the following dimensions: listening and understanding lectures, participating and expressing ideas, presenting, writing, and reading. Moreover, students have identified another set of difficulties, which is technical barriers based on educational background and the ability to deal with advanced software tools.

Ochwa-Echel, James R. "Gender gap in computer science education : experiences of women in Uganda /." View abstract, 2005. http://wwwlib.umi.com/dissertations/fullcit/3191711.

Kelkar, Shreeharsh. "Platformizing higher education : computer science and the making of MOOC infrastructures." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107312.

Behnam, Humam, and Artin Mirzaian. "Evaluation of template-based programming question generation for Computer Science education." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280114.

Chiang, Yen-Hsi. "Advising module: Graduate application system for the Computer Science Graduate Program." CSUSB ScholarWorks, 2005. https://scholarworks.lib.csusb.edu/etd-project/2725.

Turner, Scott Alexander. "minimUML: A Minimalist Approach to UML Diagraming for Early Computer Science Education." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/33030.

Acton, Donald, Kimberly Voll, Steven Wolfman, and Benjamin Yu. "Pedagogical Transformations in the UBC CS Science Education Initiative." ACM, 2009. http://hdl.handle.net/2429/8884.

Barton, Roy. "Computers and practical work in science education : a comparative study." Thesis, University of East Anglia, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318020.

Jamwal, Goldee. "Effective use of Interactive Learning Modules in Classroom Study for Computer Science Education." DigitalCommons@USU, 2012. http://digitalcommons.usu.edu/etd/1358.

Rimington, Keith B. "Expanding the Horizons of Educational Pair Programming: A Methodological Review of Pair Programming in Computer Science Education Research." DigitalCommons@USU, 2010. https://digitalcommons.usu.edu/etd/601.

Nivens, Ryan Andrew, and Rosemary Geiken. "Using a Computer Science-Based Board Game to Develop Preschoolers' Mathematics." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etsu-works/214.

Bell, Richard Scott. "Low overhead methods for improving education capacity and outcomes in computer science." Diss., Kansas State University, 2014. http://hdl.handle.net/2097/18168.

Behnke, Kara Alexandra. "Gamification in Introductory Computer Science." Thesis, University of Colorado at Boulder, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3743653.

This thesis investigates the impact of gamification on student motivation and learning in several introductory computer science educational activities. The use of game design techniques in education offers the potential to make learning more motivating and more enjoyable for students. However, the design, implementation, and evaluation of game elements that actually realize this promise remains a largely unmet challenge. This research examines whether the introduction of game elements into curriculum positively impacts student motivation and intended learning outcomes for entry-level computer science education in four settings that apply similar game design techniques in different introductory computer science educational settings. The results of these studies are evaluated using mixed methods to compare the effects of game elements on student motivation and learning in both formal and non-formal learning environments.

Finch, Dylan Keifer. "Improving and Evaluating Maria: A Virtual Teaching Assistant for Computer Science Education." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/98573.

Burke, Lauren. "Computer Science Education at The Claremont Colleges: The Building of an Intuition." Scholarship @ Claremont, 2016. http://scholarship.claremont.edu/scripps_theses/875.

Crosier, Joanna. "Virtual environments for science education : a schools-based development." Thesis, University of Nottingham, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323181.

Saw, Yihui. "Enlight : a projected augmented reality approach to science education." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/100671.

Furby, Thomas H. "A comparison of Workforce Education/Human Resource faculty and Computer Science faculty perceptions towards distance education /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1147198101&sid=16&Fmt=2&clientId=1509&RQT=309&VName=PQD.

Hunter, Jeffrey C. "Student Engagement in a Computer Rich Science Classroom." Ohio University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1426713813.

Prayaga, Lakshmi. "Game development environment to teach computer science concepts." [Pensacola, Fla.] : University of West Florida, 2007. http://purl.fcla.edu/fcla/etd/WFE0000089.

Polycarpou, Irene. "An Innovative Approach to Teaching Structural Induction for Computer Science." FIU Digital Commons, 2008. http://digitalcommons.fiu.edu/etd/18.

Wiggberg, Mattias. "Computer Science Project Courses : Contrasting Students’ Experiences with Teachers’ Expectations." Doctoral thesis, Uppsala universitet, Avdelningen för datorteknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-120081.

DeVaney, Jonah E. "tidyTouch: An Interactive Visualization Tool for Data Science Education." Digital Commons @ East Tennessee State University, 2020. https://dc.etsu.edu/honors/529.

Hewner, Michael. "Student conceptions about the field of computer science." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45890.

Bushey, Dean E. "Critical thinking traits of top-tier experts and implications for computer science education." Connect to this title online, 2007. http://etd.lib.clemson.edu/documents/1193079316/.

Jakupovic, Jasmin. "Educated to Learn : How to enhance the education of computer science and informatics." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH. Forskningsmiljö Datavetenskap och informatik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-31902.

Nivens, Ryan Andrew, and Rosemary Geiken. "Using a Computer Science-based Board Game to Develop Preschoolers' Mathematics." Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etsu-works/3040.

Sheldon, Daniel K. (Daniel Kenneth) 1974. "Computer assisted group decision making for education program development." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80120.

Maczka, Darren Kurtis. "Computing Trajectories: Pathways into Computer Science and Programming Experience in the First Year." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/92198.

Universities Have a Computer-Science Problem

The case for teaching coders to speak French

Photo of college students working at their computers as part of a hackathon at Berkeley in 2018

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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.

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