Meet the ART-AI students and read about their research interests and backgrounds.
James Proudfoot
Understanding Transfer Learning through the Calculation of Chemical Reaction Barriers
Tom Cannon
Task Agnostic Efficient and Adaptive Edge Devices Using Hierarchical Reinforcement Learning, Task Inference and Transfer Learning
Robert Clarke
Towards Intuitive Embodied BCI Robotic Manipulators Using Dynamic Visual and Kinaesthetic Imagery
Jack McKinlay
Developing Verifiable Normative Metrics for Human Centric Explainable Artificial Intelligence
Yue Zhang
Improve Perceived Trustworthiness and Fairness in Automated Decision-Making: The Role of Mental Models
Edward Clark
Artificial Intelligence Tactical Decision Aid for Management of Naval Sensors and Autonomous Vehicles
Deborah Morgan
The role of anticipatory regulatory instruments within the regulation of AI systems. A comparative study of regulatory sandbox schemes.
Alice Parfett
Using History to Predict and Prevent Negative Outcomes of Population-Wide Racial Biometric Classification Systems
Brier Rigby Dames
Discovering Transcriptional Signatures of Brain Ageing and Neurodegenerative Diseases Using Machine Learning
Oscar Bryan
Machine Learning for the Detection of Unexploded Ordnance Using Synthetic Aperture Sonar
Jack E. Saunders
Reactive Collision Avoidance Using Deep Reinforcement Learning for the Application of UAV Delivery