Our Students

Meet the ART-AI students and read about their research interests and backgrounds.


2023 Cohort

Isaac Beaglehole

Isaac Beaglehole

Machine Learning for Predictions of Pharmaceutically Important Chemical Reactions

Djordje Bozic

Djordje Bozic

Hierarchical and Intrinsically Motivated Reinforcement Learning

Eimear Curran

Eimear Curran

Machine Learning for Sensing and Control of Dynamic Stall in Realistic Conditions

Scarllette Ellis

Scarllette Ellis

Unifying Graph and Information Theory Subgoal Discovery Methods in Reinforcement Learning

Giaan Kler-Young

Giaan Kler-Young

Understanding the Impact of Pollutants on Aquatic Systems: Machine Learning, Predictive Toxicology and Transport Mechanisms

Greg Knowles

Greg Knowles

AI-based Mobility Monitoring of Axial Spondyloarthritis (AxSpA) Patients Using Wearable Sensors

Balazs Nyiro

Balazs Nyiro

AI for Next-generation Neurotechnology

Panayiotis Panayiotou

Panayiotis Panayiotou

Causal representations in Reinforcement Learning

Owen Parsons

Owen Parsons

Investigating RLHF as an alignment technique

Viraj Patel

Viraj Patel

Enhancing ultrasound images with physics-informed neural networks

Miles Pemberton

Miles Pemberton

Machine Learning Transition State Geometries

Dona Shaji

Dona Shaji

Accountable and responsible logistics optimisation via distributed AI

Rungano Sibanda

Rungano Sibanda

Automated bias in automated decision making systems

Melissa Torgbi

Melissa Torgbi

Explainable Natural Language Processing for the Analysis of Online Discourse

Brian Wiley

Brian Wiley

Studies of oxygen transport & human oxygenases via computer simulation and machine learning

Xuying Zhong

Xuying Zhong

Rendering AI more transparent and explainable: which explanations do humans prefer?

2022 Cohort

Eoin Cremen

Eoin Cremen

AI & Decision Making within Healthcare

Madalin Facino

Madalin Facino

Empathetic, Interpretable, and Explainable AI

Adam Hayes

Adam Hayes

Physics Based Learning for Weather Predictions

Joseph Marvin Imperial

Joseph Marvin Imperial

Towards Transparent and User-Centric Models for Readability Assessment

James Proudfoot

James Proudfoot

Understanding Transfer Learning through the Calculation of Chemical Reaction Barriers

Karolis Ramanauskas

Karolis Ramanauskas

Reinforcement Learning Interpretability

Jack Sharples

Jack Sharples

Bioinspired Robotic Cognitive Architecture for Understanding Human Actions

Jinha Yoon

Jinha Yoon

AI, Decision-Making, Emotion, VR: Maximising results and effectivity in human-AI coordination and cooperation

2021 Cohort

Dan Beechey

Dan Beechey

Explaining Decision Making in Reinforcement Learning

Tom Cannon

Tom Cannon

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

Robert Clarke

Robert Clarke

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

James Elson

James Elson

Autonomous Option Discovery in Hierarchical Reinforcement Learning

Harshinee Goordoyal

Harshinee Goordoyal

Machine Learning for Predictions of Haemodynamics in Cardiovascular Devices

Sophia Jones

Sophia Jones

Algorithms for AI Inspired by the Bounded Rationality of Humans

Ferdie Krammer

Ferdie Krammer

Big Data and Machine Learning for Reaction Design

Toby Lewis-Atwell

Toby Lewis-Atwell

A Transparent Machine Learning Approach to Chemical Safety Assessment

Jack McKinlay

Jack McKinlay

Value Alignment for Opaque Agents Using Preference Estimation Models

Ben Rogers

Ben Rogers

Neural Network Optimisation of Auxetics

Tom Ryder

Tom Ryder

EEG Based Brain Signal Processing and Applications using Statistical Machine Learning

Shashank Sharma

Shashank Sharma

Hierarchical Reinforcement Learning For Natural Language

Todd van Steenwyk

Todd van Steenwyk

Deep Reinforcement Learning for Asset Pricing: A Value Investing Approach

Joshua Tenn

Joshua Tenn

Debiasing AI Advice-Taking in Human-AI Collaborative Decisions

Doug Tilley

Doug Tilley

Smart Cyber-Physical Systems for Multimodal Human-Robot Collaboration

Syeda Gulnoor Zahra

Syeda Gulnoor Zahra

Algorithmic Auditing

2020 Cohort

Edward Clark

Edward Clark

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

Thao Do

Thao Do

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

Tom Donnelly

Tom Donnelly

Artificial Intelligence for the Control of Upper Limb Prosthetics

Andy Evans

Andy Evans

AI and its Consequences for the Labour Market

Tory Frame

Tory Frame

Enhancing Adult Sleep with AI

Joe Goodier

Joe Goodier

Interpretable Diagnostic Imaging Using Generative Priors

Finn Hambly

Finn Hambly

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

Matt Hewitt

Matt Hewitt

Hierarchical Reinforcement Learning for Transparency in AI

Emma Li

Emma Li

Improved Interpretability Methods Towards More Responsible AI

Pablo Medina

Pablo Medina

Persuasion-Aware Systems for Dialogue-Based Negotiation

Deborah Morgan

Deborah Morgan

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

Jessica Nicholson

Jessica Nicholson

Representation Learning of Novel Goals for Intrinsic Motivation

Alice Parfett

Alice Parfett

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

Brier Rigby Dames

Brier Rigby Dames

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

Alex Taylor

Alex Taylor

Machine learning in Safety Critical Engineering

Scott Wellington

Scott Wellington

Decoding imagined, auditory and vocalised speech from invasive and non-invasive brain signals

2019 Cohort

Oscar Bryan

Oscar Bryan

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

George Fletcher

George Fletcher

Intelligent 3D Character Creation & Animation

Catriona Gray

Catriona Gray

Knowledge, value and risk in AI governance

Akshil Patel

Akshil Patel

Improving Control with Intrinsically Motivated Reinforcement Learning

Mafalda Ribeiro

Mafalda Ribeiro

AI-Inspired Closed Loop Electrical Neuromodulation in Multiple Domains

Elena Safrygina

Elena Safrygina

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

Jack E. Saunders

Jack E. Saunders

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

Jack R. Saunders

Jack R. Saunders

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

Elsa Zhong

Elsa Zhong

How AI May Influence Human Judgement and Decision Making

Damian Ziubroniewicz

Damian Ziubroniewicz

Fair Machine Learning