Research projects
Find a postgraduate research project in your area of interest by exploring the research projects that we offer in the Department of Computer Science.
We have a broad range of research projects for which we are seeking doctoral students. Browse the list of projects on this page or follow the links below to find information on doctoral training opportunities, or applying for a postgraduate research programme.
Alternatively, if you would like to propose your own project then please include a research project proposal and the name of a possible supervisor with your application.
Available projects
Future computing systems projects
- A Multi-Tenancy FPGA Cloud Infrastructure and Runtime System
- A New Generation of Terahertz Emitters: Exploiting Electron Spin
- Balancing security and privacy with data usefulness and efficiency in wireless sensor networks
- Blockchain-based Local Energy Markets
- Cloud Computing Security
- Design and Exploration of a Memristor-enabled FPGA Architecture
- Design and Implementation of an FPGA-Accelerated Data Analytics Database
- Designing Safe & Explainable Neural Models in NLP
- Dynamic Resource Management for Intelligent Transportation System Applications
- Evaluating Systems for the Augmentation of Human Cognition
- Exploring Unikernel Operating Systems Running on reconfigurable Softcore Processors
- Finding a way through the Fog from the Edge to the Cloud
- Guaranteeing Reliability for IoT Edge Computing Systems
- Hardware Aware Training for AI Systems
- Hybrid Fuzzing Concurrent Software using Model Checking and Machine Learning
- Job and Task Scheduling and Resource Allocation on Parallel/Distributed systems including Cloud, Edge, Fog Computing
- Machine Learning with Bio-Inspired Neural Networks
- Managing the data deluge for Big Data, Internet-of-Things and/or Industry 4.0 environments
- Pervasive Technology for Multimodal Human Memory Augmentation
- Power Management Methodologies for IoT Edge Devices
- Power Transfer Methods for Inductively Coupled 3-D ICs
- Problems in large graphs representing social networks
- Programmable Mixed-Signal Fabric for Machine Learning Applications
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing
- Security and privacy in p2p electricity trading
- Skyrmion-based Electronics
- Smart Security for Smart Services in an IoT Context
- Spin waves dynamics for spintronic computational devices
- Technology-driven Human Memory Degradation
- Ultrafast spintronics with synthetic antiferromagnets
Human centred computing projects
- Advising on the Use and Misuse of Collaborative Coding Workflows
- Automatic Activity Analysis, Detection and Recognition
- Automatic Emotion Detection, Analysis and Recognition
- Automatic Experimental Design with Human in the Loop (2025 entry onward)
- Biases in Physical Activity Tracking
- Computer Graphics - Material Appearance Modeling and Physically Based Rendering
- Design principles for glancing at information by visually disabled users
- Evaluating Systems for the Augmentation of Human Cognition
- Extending Behavioural Algorithmics as a Predictor of Type 1 Diabetes Blood Glucose Highs
- Geo-location as a Predictor of Type 1 Diabetes Blood Glucose
- Learning of user models in human-in-the-loop machine learning (2025 entry onward)
- Machine Learning and Cognitive Modelling Applied to Video Games
- Models of Bio-Sensed Body Temperature and Environment as a Refinement of Type 1 Diabetes Blood Glucose Prediction Algorithmics
- Music Generation and Information Processing via Deep Learning
- Pervasive Technology for Multimodal Human Memory Augmentation
- Smart Security for Smart Services in an IoT Context
- Technology-driven Human Memory Degradation
- Understanding the role of the Web on Memory for Programming Concepts
- User Modeling for Physical Activity Tracking
Artificial intelligence projects
- (MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
- Abstractive multi-document summarisation
- Applying Natural Language Processing to real-world patient data to optimise cancer care
- Automated Repair of Deep Neural Networks
- Automatic Activity Analysis, Detection and Recognition
- Automatic Emotion Detection, Analysis and Recognition
- Automatic Experimental Design with Human in the Loop (2025 entry onward)
- Automatic Learning of Latent Force Models
- Balancing security and privacy with data usefulness and efficiency in wireless sensor networks
- Biologically-Plausible Continual Learning
- Cognitive Robotics and Human Robot Interaction
- Collaborative Probabilistic Machine Learning (2025 entry onward)
- Computational Modelling of Child Language Learning
- Contextualised Multimedia Information Retrieval via Representation Learning
- Controlled Synthesis of Virtual Patient Populations with Multimodal Representation Learning
- Data Integration & Exploration on Data Lakes
- Data Lake Exploration with Modern Artificial Intelligence Techniques
- Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
- Deep Learning for Temporal Information Processing
- Design and Implementation of an FPGA-Accelerated Data Analytics Database
- Designing Safe & Explainable Neural Models in NLP
- Ensemble Strategies for Semi-Supervised, Unsupervised and Transfer Learning
- Event Coreference at Document Level
- Explainable and Interpretable Machine Learning
- Formal Verification for Robot Swams and Wireless Sensor Networks
- Formal Verification of Robot Teams or Human Robot Interaction
- Foundations and Advancement of Subontology Generation for Clinically Relevant Information
- Generating Goals from Responsibilities for Long Term Autonomy
- Generating explainable answers to fact verification questions
- Hardware Aware Training for AI Systems
- Hybrid Fuzzing Concurrent Software using Model Checking and Machine Learning
- Integrated text and table mining
- Interpretable machine learning for healthcare applications
- Job and Task Scheduling and Resource Allocation on Parallel/Distributed systems including Cloud, Edge, Fog Computing
- Knowledge Graph Construction via Learning and Reasoning
- Knowledge Graph for Guidance and Explainability in Machine Learning
- Learning of user models in human-in-the-loop machine learning (2025 entry onward)
- Machine Learning and Cognitive Modelling Applied to Video Games
- Machine Learning for Vision and Language Understanding
- Machine Learning with Bio-Inspired Neural Networks
- Multi-task Learning and Applications
- Music Generation and Information Processing via Deep Learning
- Neuro-sybolic theorem proving
- Ontology Informed Machine Learning for Computer Vision
- Optimization and verification of systems modelled using neural networks
- Probabilistic modelling and Bayesian machine learning (2025 entry onward)
- Problems in large graphs representing social networks
- Programmable Mixed-Signal Fabric for Machine Learning Applications
- Representation Learning and Its Applications
- Skyrmion-based Electronics
- Smart Security for Smart Services in an IoT Context
- Software verification with contrained Horn clauses and first-order theorem provers
- Solving PDEs via Deep Neural Nets: Underpinning Accelerated Cardiovascular Flow Modelling with Learning Theory
- Solving mathematical problems using automated theorem provers
- Solving non-linear constraints over continuous functions
- Symmetries and Automated Theorem Proving
- Text Analytics and Blog/Forum Analysis
- Theorem Proving for Temporal Logics
- Trustworthy Multi-source Learning (2025 entry onward)
- Verification Based Model Extraction Attack and Defence for Deep Neural Networks
- Zero-Shot Learning and Applications
Software and e-infrastructure projects
- Advising on the Use and Misuse of Collaborative Coding Workflows
- Automatic Detection and Repair of Software Vulnerabilities in Unmanned Aerial Vehicles
- Combining Concolic Testing with Machine Learning to Find Software Vulnerabilities in the Internet of Things
- Component-based Software Development.
- Design and Exploration of a Memristor-enabled FPGA Architecture
- Dynamic Resource Management for Intelligent Transportation System Applications
- Effective Teaching of Programming: A Detailed Investigation
- Exploiting Software Vulnerabilities at Large Scale
- Extending Behavioural Algorithmics as a Predictor of Type 1 Diabetes Blood Glucose Highs
- Finding Vulnerabilities in IoT Software using Fuzzing, Symbolic Execution and Abstract Interpretation
- Geo-location as a Predictor of Type 1 Diabetes Blood Glucose
- Job and Task Scheduling and Resource Allocation on Parallel/Distributed systems including Cloud, Edge, Fog Computing
- Managing the data deluge for Big Data, Internet-of-Things and/or Industry 4.0 environments
- Models of Bio-Sensed Body Temperature and Environment as a Refinement of Type 1 Diabetes Blood Glucose Prediction Algorithmics
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing
- Security and privacy in p2p electricity trading
- Using Program Synthesis for Program Repair in IoT Security
- Verification Based Model Extraction Attack and Defence for Deep Neural Networks
- Verifying Cyber-attacks in CUDA Deep Neural Networks for Self-Driving Cars
Theory and foundations projects
- A Multi-Tenancy FPGA Cloud Infrastructure and Runtime System
- Application Level Verification of Solidity Smart Contracts
- Automated Repair of Deep Neural Networks
- Automatic Detection and Repair of Software Vulnerabilities in Unmanned Aerial Vehicles
- Blockchain-based Local Energy Markets
- Categorical proof theory
- Combining Concolic Testing with Machine Learning to Find Software Vulnerabilities in the Internet of Things
- Exploiting Software Vulnerabilities at Large Scale
- Finding Vulnerabilities in IoT Software using Fuzzing, Symbolic Execution and Abstract Interpretation
- Formal Methods: Hybrid Event-B and Rodin
- Formal Methods: Mechanically Checking the Semantics of Hybrid Event-B
- Formal Semantics of the Perfect Language
- Formal Verification for Robot Swams and Wireless Sensor Networks
- Formal Verification of Robot Teams or Human Robot Interaction
- Foundations and Advancement of Subontology Generation for Clinically Relevant Information
- Hybrid Fuzzing Concurrent Software using Model Checking and Machine Learning
- Interpretable machine learning for healthcare applications
- Machine Learning with Bio-Inspired Neural Networks
- Mathematical models for concurrent systems
- Neuro-sybolic theorem proving
- Optimization and verification of systems modelled using neural networks
- Problems in large graphs representing social networks
- Security and privacy in p2p electricity trading
- Software verification with contrained Horn clauses and first-order theorem provers
- Solving PDEs via Deep Neural Nets: Underpinning Accelerated Cardiovascular Flow Modelling with Learning Theory
- Solving mathematical problems using automated theorem provers
- Solving non-linear constraints over continuous functions
- Symmetries and Automated Theorem Proving
- Theorem Proving for Temporal Logics
- Trustworthy Multi-source Learning (2025 entry onward)
- Using Program Synthesis for Program Repair in IoT Security
- Verifying Cyber-attacks in CUDA Deep Neural Networks for Self-Driving Cars
James Elson projects
Data science projects
- (MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
- Applying Natural Language Processing to real-world patient data to optimise cancer care
- Automated Repair of Deep Neural Networks
- Automatic Activity Analysis, Detection and Recognition
- Automatic Emotion Detection, Analysis and Recognition
- Automatic Experimental Design with Human in the Loop (2025 entry onward)
- Automatic Learning of Latent Force Models
- Blockchain-based Local Energy Markets
- Collaborative Probabilistic Machine Learning (2025 entry onward)
- Contextualised Multimedia Information Retrieval via Representation Learning
- Controlled Synthesis of Virtual Patient Populations with Multimodal Representation Learning
- Data Integration & Exploration on Data Lakes
- Data Lake Exploration with Modern Artificial Intelligence Techniques
- Data Wrangling
- Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
- Deep Learning for Temporal Information Processing
- Design and Implementation of an FPGA-Accelerated Data Analytics Database
- Dynamic Resource Management for Intelligent Transportation System Applications
- Ensemble Strategies for Semi-Supervised, Unsupervised and Transfer Learning
- Explainable and Interpretable Machine Learning
- Extending Behavioural Algorithmics as a Predictor of Type 1 Diabetes Blood Glucose Highs
- Finding a way through the Fog from the Edge to the Cloud
- Fishing in the Data Lake
- Geo-location as a Predictor of Type 1 Diabetes Blood Glucose
- Hardware Aware Training for AI Systems
- Integrated text and table mining
- Interpretable machine learning for healthcare applications
- Knowledge Graph Construction via Learning and Reasoning
- Knowledge Graph for Guidance and Explainability in Machine Learning
- Learning of user models in human-in-the-loop machine learning (2025 entry onward)
- Machine Learning and Cognitive Modelling Applied to Video Games
- Machine Learning with Bio-Inspired Neural Networks
- Managing the data deluge for Big Data, Internet-of-Things and/or Industry 4.0 environments
- Models of Bio-Sensed Body Temperature and Environment as a Refinement of Type 1 Diabetes Blood Glucose Prediction Algorithmics
- Multi-task Learning and Applications
- Music Generation and Information Processing via Deep Learning
- Probabilistic modelling and Bayesian machine learning (2025 entry onward)
- Problems in large graphs representing social networks
- Representation Learning and Its Applications
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing
- Security and privacy in p2p electricity trading
- Specifying and Optimising Data Wrangling Tasks
- Text Analytics and Blog/Forum Analysis
- Trustworthy Multi-source Learning (2025 entry onward)
- Verification Based Model Extraction Attack and Defence for Deep Neural Networks
- Zero-Shot Learning and Applications
Sophia Ananiadou projects
Mauricio Alvarez projects
Richard Banach projects
Riza Batista-navarro projects
Ke Chen projects
- Automatic Activity Analysis, Detection and Recognition
- Automatic Emotion Detection, Analysis and Recognition
- Biologically-Plausible Continual Learning
- Contextualised Multimedia Information Retrieval via Representation Learning
- Deep Learning for Temporal Information Processing
- Ensemble Strategies for Semi-Supervised, Unsupervised and Transfer Learning
- Explainable and Interpretable Machine Learning
- Machine Learning and Cognitive Modelling Applied to Video Games
- Multi-task Learning and Applications
- Music Generation and Information Processing via Deep Learning
- Zero-Shot Learning and Applications
Sarah Clinch projects
Angelo Cangelosi projects
Jiaoyan Chen projects
Lucas Cordeiro projects
- Application Level Verification of Solidity Smart Contracts
- Automated Repair of Deep Neural Networks
- Automatic Detection and Repair of Software Vulnerabilities in Unmanned Aerial Vehicles
- Combining Concolic Testing with Machine Learning to Find Software Vulnerabilities in the Internet of Things
- Designing Safe & Explainable Neural Models in NLP
- Exploiting Software Vulnerabilities at Large Scale
- Finding Vulnerabilities in IoT Software using Fuzzing, Symbolic Execution and Abstract Interpretation
- Hybrid Fuzzing Concurrent Software using Model Checking and Machine Learning
- Using Program Synthesis for Program Repair in IoT Security
- Verification Based Model Extraction Attack and Defence for Deep Neural Networks
- Verifying Cyber-attacks in CUDA Deep Neural Networks for Self-Driving Cars
Louise Dennis projects
Clare Dixon projects
Suzanne Embury projects
Marie Farrell projects
Alejandro Frangi projects
Andre Freitas projects
Michael Fisher projects
Gareth Henshall projects
Simon Harper projects
Caroline Jay projects
Samuel Kaski projects
- Automatic Experimental Design with Human in the Loop (2025 entry onward)
- Collaborative Probabilistic Machine Learning (2025 entry onward)
- Learning of user models in human-in-the-loop machine learning (2025 entry onward)
- Probabilistic modelling and Bayesian machine learning (2025 entry onward)
- Trustworthy Multi-source Learning (2025 entry onward)
Dirk Koch projects
Konstantin Korovin projects
- Neuro-sybolic theorem proving
- Optimization and verification of systems modelled using neural networks
- Software verification with contrained Horn clauses and first-order theorem provers
- Solving mathematical problems using automated theorem provers
- Solving non-linear constraints over continuous functions
- Symmetries and Automated Theorem Proving
Kung-kiu Lau projects
Zahra Montazeri projects
Christoforos Moutafis projects
Tingting Mu projects
Anirbit Mukherjee projects
Mustafa Mustafa projects
Goran Nenadic projects
- (MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
- Applying Natural Language Processing to real-world patient data to optimise cancer care
- Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
- Integrated text and table mining
- Text Analytics and Blog/Forum Analysis
Paul Nutter projects
- A New Generation of Terahertz Emitters: Exploiting Electron Spin
- Effective Teaching of Programming: A Detailed Investigation
- Extending Behavioural Algorithmics as a Predictor of Type 1 Diabetes Blood Glucose Highs
- Geo-location as a Predictor of Type 1 Diabetes Blood Glucose
- Models of Bio-Sensed Body Temperature and Environment as a Refinement of Type 1 Diabetes Blood Glucose Prediction Algorithmics
Nhung Nguyen projects
Pierre Olivier projects
Norman Paton projects
Vasilis Pavlidis projects
Pavlos Petoumenos projects
Steve Pettifer projects
Oliver Rhodes projects
Giles Reger projects
Rizos Sakellariou projects
- Dynamic Resource Management for Intelligent Transportation System Applications
- Finding a way through the Fog from the Edge to the Cloud
- Job and Task Scheduling and Resource Allocation on Parallel/Distributed systems including Cloud, Edge, Fog Computing
- Managing the data deluge for Big Data, Internet-of-Things and/or Industry 4.0 environments
- Problems in large graphs representing social networks
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing