I am a PhD student working on the collaborative content creation use case as part of the UKRI research project PHAWM (Participatory Harm Auditing Workbenches and Methodologies), while also being aligned with the UKRI Centre for Doctoral Training in Safe and Trusted...
My research focuses on developing AI-supported technologies that strengthen mental health and wellbeing in the everyday lives of young people and families. I work within human–computer interaction, exploring how generative AI tools can scaffold everyday psychological...
I am a PhD student in Computer Science Research at Imperial and King’s College London. My research mainly focuses on mechanistic interpretability and robustness in LLMs. I have a broad interdisciplinary background in cognitive psychology, philosophy, and...
My research topic is ‘Interpretable Spatio-Temporal Crime Prediction Models Based on Machine Learning’. This study aims to develop interpretable spatio-temporal crime prediction models in London. Current crime prediction models struggle to balance...
Ensuring that reinforcement learning emits policies that are safe and verifiable is crucial, and my project aims to do so through integrating Formal Methods, such as using temporal logic to shield the policy from performing unsafe action or synthetising reward...
I’m doing my PhD at Imperial on learning from action-free videos, adapted for unseen and open-ended environments by leveraging generative AI. My research focuses on enhancing learning from expert demonstrations in a scalable and interpretable way, contributing...
My background is in the theory of deep learning, and during my PhD, I aim to use ideas of functional similarity and mechanistic interpretability to better understand neural networks and their outputs from a foundational perspective. My previous research has focused on...
