I’m a fourth-year DPhil student at the University of Oxford, where I am co-supervised by Jakob Foerster and Shimon Whiteson. I’m also a member of the AIMS CDT.
I recently completed a research internship at Wayve, working in the World Models Team on video generation for autonomous vehicles. Previously, I completed SWE internships at Amazon, Arm, and Cubica.
Research
Currently, I’m exploring how VLMs can improve RL (synthetic data, representation learning), and how RL can improve VLMs (reasoning, tool-use).
I have published work on offline, meta, and open-ended RL, as well as diffusion models and plasticity.
Policy-Guided Diffusion
RLC 2024 - NeurIPS 2023 Workshop on Robot Learning   paper
Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps
NeurIPS 2024   paper
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
NeurIPS 2023   paper
Further Publications
Can Learned Optimization Make Reinforcement Learning Less Difficult?
NeurIPS 2024 (Spotlight)   paper
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning
ICML 2024 (Spotlight)   paper
Risks and Opportunities of Open Source Generative AI
ICML 2024 (Oral)   paper
SplAgger: Split Aggregation for Meta-Reinforcement Learning
RLC 2024   paper
Retrieve What You Need: A Mutual Learning Framework for Open-domain Question Answering
TACL 2024   paper
Online Reinforcement Learning Controllers for Soft Robots using Learned Environments
RoboSoft 2024
Hypernetworks in Meta-Reinforcement Learning
CoRL 2022   paper
Multi-Modal Fusion by Meta-Initialization
FARSCOPE Robotics Workshop 2022 (Best Poster Award)   paper