Hello!
I am a postdoctoral research fellow at the University of British Columbia and the Vector Institute supervised by Prof. Jeff Clune. I am interested in developing autonomous agents that are safe, curious and can learn in an open-ended manner, particularly driven by recent advances in large language or multimodal models together with deep reinforcement learning.
I previously received my PhD at the University of Oxford supervised by Prof. Michael A. Osborne and Prof. Yee Whye Teh. During the PhD, I was particularly interested in offline reinforcement learning with work in generalization to unseen tasks, uncertainty quantification for offline world models, and learning from pixels. Our most recent work concerned efficiently training RL agents using synthetic data! Please do feel free to reach out!
You can find my PhD thesis here!
Recent News
- [4/2024] Our work on language-guided control won an outstanding paper award at the GenAI4DM Workshop!
- [1/2024] Excited to begin my postdoc at the University of British Columbia working on open-endedness!
- [11/2023] 2 papers accepted at NeurIPS workshops, on edge-of-reach problems in offline MBRL and on-policy guided synthetic data generation!
- [10/2023] Excited to rejoin Waymo Research on the Sim Agents team!
- [9/2023] New work: Synthetic Experience Replay - arbtrarily upsampling an agent's experiences accepted at NeurIPS. See you in New Orleans!
- [8/2023] Challenges and opportunities in offline reinforcement learning from visual observations accepted at TMLR.
- [12/2022] Internship project at MSR Cambridge on automated game testing using Go-Explore accepted at IEEE ToG.
- [8/2022] I am interning at Waymo Research supervised by Max Igl.
- [6/2022] Our work on offline RL from pixels won the Best Paper Award at L-DOD.
- [5/2022] Our work on PBT across architectures and hyperparameters was accepted at AutoML.
- [3/2022] I am interning at MSR Cambridge in the Deep RL for Games group.
- [2/2022] Our work on revisiting design choices in offline model-based reinforcement learning received a Spotlight at ICLR!