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. 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

[Aug 2024] I have joined the Goal-Oriented Autonomous Long-Lived Systems (GOALS) group at the Oxford Robotics Institute as a Postdoctoral Researcher. I am excited to continue my work on reinforcement learning and planning, dive into robotics applications, and develop graph learning techniques for autonomous systems.

[Aug 2024] Our work Trust-based Consensus in Multi-Agent Reinforcement Learning Systems was presented at the First Reinforcement Learning Conference (RLC). In this paper, we propose a trust mechanism for dealing with unreliable actors in decentralized multi-agent systems, and empirically show its effectiveness for solving a set of consensus environments. You can find a short video about the work here.

[Jul 2024] Our paper A Graph Reinforcement Learning framework for neural Adaptive Large Neighbourhood Search is now published in Computers & Operations Research. We propose a hybrid method that combines Graph RL and the ALNS metaheuristic, improving significantly on classic mechanisms as well as recently proposed RL techniques.