Education

My research interests revolve around reinforcement learning and generative model reasoning. I am exploring ways to improve policy optimisation with policy gradients and expectation maximisation. I want to push the boundaries of world models and how they can support reasoning models (not limited to or even focused on LLM's, but also control, robotics, physics, gaming).

Attended
- Poster TAROS 2026, UKAIRS 2026
- Learning Theory Summer School (June 22-25, 2026)
Teaching Assistant
- COMP38311 Advanced Distributed Systems
- COMP63101 Formal Methods for Software Verification Security and Computer Science
- COMP16321 Introduction to Programming

Interpret complex data, communicate insights effectively, and solve business challenges using evidence-based decision-making, in order to influence decisions and deliver analytical projects in today’s data-focused organisations, alongside expertise in business intelligence, forecasting, machine learning, optimisation, and project management.

Dissertation on Dynamic Time-Warping for clustering market data to enhance investment strategies by identifying asynchronous market patterns.

Deep-diving into statistics (Larry Wasserman) and probability (Bertsekas, Tsitsiklis) and their use in machine learning and data science - building understanding from the fundamental theory up.

Took off the theoretical engineer hat and put on the real-world problem-solving hat, where ethics, policy and business goals take centre stage. Connected over six weeks with individuals from across the world, learning many new perspectives on artificial intelligence and its deployment at scale.

Science of psychology, exploring the richness of human functions, uncovering the brain’s secrets, and revealing its complexities. Studies from the biological, psychodynamic, cognitive, behavioural and social approaches are presented.