I am a PostDoc in the ProrokLab at the University of Cambridge, Department of Computer Science and Technology, and a PostDoctoral By-Fellow at Churchill College. My current research focuses on watermarking for robotics. Our ICLR 2026 robot watermarking paper, introduces the first iteration of a watermark for robot policies that can be detected from video alone. In parallel, I also work on learning heterogeneous behaviour in multi-robot systems.

Before this, I completed my PhD in the Adaptive and Intelligent Robotics Lab at Imperial College London, Department of Computing, under the supervision of Prof Antoine Cully. My PhD research focused on Quality-Diversity (QD) algorithms, particularly in uncertain environments, as well as Deep Reinforcement Learning and how these two approaches can complement each other. If you are interested in what I mean by QD in uncertain environments, have a look at our Extract-QD paper. It summarises this part of our research and won the GECCO 2025 Best Paper Award! My PhD thesis on the topic also received the ACM SIGEVO Outstanding Dissertation Award.

In 2023, I interrupted my PhD to work as a Research Assistant on DARPA’s Learning Introspective Control (LINC). We developed a pipeline for online learning that allows robots to recover from damage in a few seconds. More details in our Nature Communications paper Getting Robots Back on Track.

Alongside my PhD, I also worked part-time as a Teaching Scholar in the Department of Computing at Imperial, spending about one third of my time on teaching activities in parallel with my research. I was also part of the organising committee for the ICARL seminars. You can find more about my teaching experience on my Teaching page.