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
- (MRC DTP) Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
- (MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
- A Multi-Tenancy FPGA Cloud Infrastructure and Runtime System
- A New Generation of Terahertz Emitters: Exploiting Electron Spin
- Arousal and Scanpath Trend Analysis (a-STA)
- 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
- Evaluating Systems for the Augmentation of Human Cognition
- Finding a way through the Fog from the Edge to the Cloud
- Guaranteeing Reliability for IoT Edge Computing Systems
- 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
- 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
- Smart Security for Smart Services in an IoT Context
- Spin waves dynamics for spintronic computational devices
- Spintronics-based Neuromorphic Computing for Deep Learning
- Technology-driven Human Memory Degradation
- Ultrafast spintronics with synthetic antiferromagnets
Human centred computing projects
- (MRC DTP) Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
- (MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
- Advising on the Use and Misuse of Collaborative Coding Workflows
- Arousal and Scanpath Trend Analysis (a-STA)
- Automatic Activity Analysis, Detection and Recognition
- Automatic Emotion Detection, Analysis and Recognition
- Computational Models to Predict Overnight Hypoglycemia in Type 1 Diabetes
- Evaluating Systems for the Augmentation of Human Cognition
- Machine Learning and Cognitive Modelling Applied to Video Games
- Machine Learning and Explainable AI (EPSRC iCASE studentship)
- Pervasive Technology for Multimodal Human Memory Augmentation
- Predicting Blood Glucose from Nutrition Analytics for Type 1 Diabeties
- Smart Security for Smart Services in an IoT Context
- Technology-driven Human Memory Degradation
- The Effect of Uncertainty when Implementing Machine Ethics
- Type 1 Diabetes: Accurate Prediction of Glucose Absorption from Food
Artificial intelligence projects
- (MRC DTP) Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
- (MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
- Abstractive multi-document summarisation
- Automatic Activity Analysis, Detection and Recognition
- Automatic Emotion Detection, Analysis and Recognition
- Balancing security and privacy with data usefulness and efficiency in wireless sensor networks
- Biologically-Plausible Continual Learning
- Building Machine Learning Models Using Matrix Factorisation
- Contextualised Multimedia Information Retrieval via Representation Learning
- Data Integration & Exploration on Data Lakes
- Deep Learning Architectures for Complex Data Fusion and Integration
- Deep Learning for Temporal Information Processing
- Design and Implementation of an FPGA-Accelerated Data Analytics Database
- Ensemble Strategies for Semi-Supervised, Unsupervised and Transfer Learning
- Event Coreference at Document Level
- Explainable AI and Dialog for Trust in Human-Robot Interaction
- Explainable and Interpretable Machine Learning
- Formal Verification for Robot Swams and Wirelss Sensor Networks
- Generating explainable answers to fact verification questions
- Integrated text and table mining
- Job and Task Scheduling and Resource Allocation on Parallel/Distributed systems including Cloud, Edge, Fog Computing
- Machine Learning and Cognitive Modelling Applied to Video Games
- Machine Learning and Explainable AI (EPSRC iCASE studentship)
- Machine Learning for Vision and Language Understanding
- Multi-task Learning and Applications
- Problems in large graphs representing social networks
- Programmable Mixed-Signal Fabric for Machine Learning Applications
- Reasoning with Natural Language
- Smart Security for Smart Services in an IoT Context
- Spintronics-based Neuromorphic Computing for Deep Learning
- Text Analytics and Blog/Forum Analysis
- The Effect of Uncertainty when Implementing Machine Ethics
- Trust and Wellbeing in Transparent Human-Robot Interaction Teams
- Zero-Shot Learning and Applications
Software and e-infrastructure projects
- (MRC DTP) Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
- (MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
- 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.
- Computational Models to Predict Overnight Hypoglycemia in Type 1 Diabetes
- Design and Exploration of a Memristor-enabled FPGA Architecture
- Exploiting Software Vulnerabilities at Large Scale
- Finding Vulnerabilities in IoT Software using Fuzzing, Symbolic Execution and Abstract Interpretation
- 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
- Predicting Blood Glucose from Nutrition Analytics for Type 1 Diabeties
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing
- Security and privacy in p2p electricity trading
- Security-Minded Verification for Autonomous Systems
- Type 1 Diabetes: Accurate Prediction of Glucose Absorption from Food
- Using Program Synthesis for Program Repair in IoT Security
- 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
- 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 Wirelss Sensor Networks
- Mathematical models for concurrent systems
- Problems in large graphs representing social networks
- Security and privacy in p2p electricity trading
- Security-Minded Verification for Autonomous Systems
- 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
- Automatic Activity Analysis, Detection and Recognition
- Automatic Emotion Detection, Analysis and Recognition
- Blockchain-based Local Energy Markets
- Building Machine Learning Models Using Matrix Factorisation
- Computational Models to Predict Overnight Hypoglycemia in Type 1 Diabetes
- Contextualised Multimedia Information Retrieval via Representation Learning
- Data Integration & Exploration on Data Lakes
- Data Wrangling
- Deep Learning for Temporal Information Processing
- Design and Implementation of an FPGA-Accelerated Data Analytics Database
- Ensemble Strategies for Semi-Supervised, Unsupervised and Transfer Learning
- Explainable and Interpretable Machine Learning
- Finding a way through the Fog from the Edge to the Cloud
- Fishing in the Data Lake
- Machine Learning and Cognitive Modelling Applied to Video Games
- Managing the data deluge for Big Data, Internet-of-Things and/or Industry 4.0 environments
- Multi-task Learning and Applications
- Predicting Blood Glucose from Nutrition Analytics for Type 1 Diabeties
- Problems in large graphs representing social networks
- 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
- Type 1 Diabetes: Accurate Prediction of Glucose Absorption from Food
- Unlocking Open Data through Wrapper Generation
- Zero-Shot Learning and Applications
Sophia Ananiadou 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
- Zero-Shot Learning and Applications
Sarah Clinch projects
Angelo Cangelosi projects
Lucas Cordeiro projects
- Application Level Verification of Solidity Smart Contracts
- 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
- Exploiting Software Vulnerabilities at Large Scale
- Finding Vulnerabilities in IoT Software using Fuzzing, Symbolic Execution and Abstract Interpretation
- Using Program Synthesis for Program Repair in IoT Security
- Verifying Cyber-attacks in CUDA Deep Neural Networks for Self-Driving Cars
Louise Dennis projects
Clare Dixon projects
Suzanne Embury projects
Andre Freitas projects
Simon Harper projects
Dirk Koch projects
Kung-kiu Lau projects
Christoforos Moutafis projects
Tingting Mu projects
Mustafa Mustafa projects
Goran Nenadic projects
- (MRC DTP) Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
- (MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
- Integrated text and table mining
- Text Analytics and Blog/Forum Analysis
Paul Nutter projects
Norman Paton projects
Vasilis Pavlidis projects
Ian Pratt-hartmann projects
Giles Reger projects
Rizos Sakellariou projects
- 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