I am a computer scientist working as a Postdoctoral Researcher at the Oxford Robotics Institute, University of Oxford, where I am a part of the GOALS group led by Nick Hawes. I am also a Retained Lecturer in Engineering Science at Jesus College and an Honorary Research Fellow at UCL Computer Science.

My primary goal is the development of artificial intelligence techniques for solving challenging decision-making problems effectively. My research interests are at the intersection of reinforcement learning and planning, graph learning, combinatorial optimization, and multi-agent systems. I am broadly interested in both fundamental research and application areas spanning robotics, operations research, computer and communication systems, and causal inference.

News

[Mar 2025] We have just publicly released code and data for several of our recent works including implementations of the CABRA, GRLOS, and PRORL methods. Head to the Publications page for links to the relevant repositories.

[Feb 2025] Our paper A Cost-Aware Adaptive Bike Repositioning Agent Using Deep Reinforcement Learning has been published in IEEE Transactions on Intelligent Transportation Systems. We propose a reinforcement learning method for balancing resources in urban bike-sharing systems (BSS) that takes into account operational costs and is evaluated with real-world data from major cities. We demonstrate its advantages over existing techniques, including in a BSS with 1765 docking stations.

[Nov 2024] We presented our work Reinforcement Learning Discovers Efficient Decentralized Graph Path Search Strategies at the Third Learning on Graphs Conference (LoG 2024). Inspired by Milgram's small world experiment, we frame the problem of path search in graphs as a decentralized multi-agent decision-making process. We propose the GARDEN method and demonstrate its advantages over heuristic and learned baselines, including on real-world social media networks.