Our Students

AI & Decision Making within Healthcare

Empathetic, Interpretable, and Explainable AI

Reliable AI for Solving Partial Differential Equations

Towards Transparent and User-Centric Models for Readability Assessment

Understanding Transfer Learning through the Calculation of Chemical Reaction Barriers

Reinforcement Learning Interpretability

Bioinspired Robotic Cognitive Architecture for Understanding Human Actions

Neural Correlates of Trust in Human-AI Interaction

Explaining Decision Making in Reinforcement Learning

Task Agnostic Efficient and Adaptive Edge Devices Using Hierarchical Reinforcement Learning, Task Inference and Transfer Learning

Towards Intuitive Embodied BCI Robotic Manipulators Using Dynamic Visual and Kinaesthetic Imagery

Autonomous Option Discovery in Hierarchical Reinforcement Learning

Machine Learning for Predictions of Haemodynamics in Cardiovascular Devices

Algorithms for AI Inspired by the Bounded Rationality of Humans

Big Data and Machine Learning for Reaction Design

A Transparent Machine Learning Approach to Chemical Safety Assessment

Developing Verifiable Normative Metrics for Human Centric Explainable Artificial Intelligence

Neural Network Optimisation of Auxetics

EEG Based Brain Signal Processing and Applications using Statistical Machine Learning

Hierarchical Reinforcement Learning For Natural Language

Measuring Corporate Risk Exposure with Machine Learning

Debiasing AI Advice-Taking in Human-AI Collaborative Decisions

Smart Cyber-Physical Systems for Multimodal Human-Robot Collaboration

Algorithmic Auditing

Improve Perceived Trustworthiness and Fairness in Automated Decision-Making: The Role of Mental Models

Artificial Intelligence Tactical Decision Aid for Management of Naval Sensors and Autonomous Vehicles

AI for Identification and Support for Victims of Sexual Exploitation in Southeast Asia

Artificial Intelligence for the Control of Upper Limb Prosthetics

AI and its Consequences for the Labour Market

Enhancing Adult Sleep with AI

Interpretable Diagnostic Imaging Using Generative Priors

Bayesian Modelling of Low-Voltage Networks and Demand-Side Management Schemes

Hierarchical Reinforcement Learning for Transparency in AI

Improved Interpretability Methods Towards More Responsible AI

Persuasion-Aware Systems for Dialogue-Based Negotiation

The role of anticipatory regulatory instruments within the regulation of AI systems. A comparative study of regulatory sandbox schemes.

Representation Learning of Novel Goals for Intrinsic Motivation

Using History to Predict and Prevent Negative Outcomes of Population-Wide Racial Biometric Classification Systems

Discovering Transcriptional Signatures of Brain Ageing and Neurodegenerative Diseases Using Machine Learning

Machine learning in Safety Critical Engineering

Decoding Imaginary and Auditory Speech Using Surface EEG

Machine Learning for the Detection of Unexploded Ordnance Using Synthetic Aperture Sonar

Intelligent 3D Character Creation & Animation

Knowledge, value and risk in AI governance

Improving Control with Intrinsically Motivated Reinforcement Learning

AI-Inspired Closed Loop Electrical Neuromodulation in Multiple Domains

Translating Spatio-Temporal Imaging Data Into Clinical Data Using Machine Learning

Reactive Collision Avoidance Using Deep Reinforcement Learning for the Application of UAV Delivery

Crossing the Uncanny Valley: Using Deep Learning for Realism in Facial Animation

How AI May Influence Human Judgement and Decision Making

Fair Machine Learning