Hey! I’ll soon be graduating as a Machine Learning D.phil student at the OATML group at University of Oxford. I’m supervised by Prof. Yarin Gal.

I’m currently working on designing methods, architectures and benchmarks to enable transformer-based agents to do long horizon tasks by creating and accessing memories, through large-scale RL.

Some of the topics I have done research on over the previous three years are:

• Leveraging advances in visual diffusion modeling for robotics
• Mechanistic interpretability in transformer-based world models
• Training generative world models for video games and robotics, and
• Causally-correct, sample-efficient learning from imbalanced data.

I also collaborated closely with researchers from Toyota Research (Adrien Gaidon and Rowan McAllister) on topics related to causal robot learning.

Prior to my Ph.D, I was a deep learning researcher at Wayve, exploring reinforcment learning algorithms on autonomous driving data. I graduated from a Machine Learning Research Master’s at Mila (Sept 2020) where I did research on meta learning, continual learning and inverse reinforcement learning. I was also an ED&I Fellow with the MPLS department at the University of Oxford in 2022-2023 cohort.

Download my resumé.