About Me

I am a PhD student at the University of Alberta in reinforcement learning, supervised by Prof. Dale Schuurmans. Before this, I was a reinforcement learning researcher at Kindred AI. I completed my MSc in Applied Computing and HBSc in Computer Science at the University of Toronto.

My life-long research goal is to create autonomous agents that can adapt continually in real life. In particular, I am interested in developing an agent that can 1) understand the properties of the world from 2) minimal interactions with environment and from 3) observing other agents’ behaviours. The more ambitious agent would be 4) curious about the world and explores to answer its own questions and have the ability to 5) build a repertoire of skills such that they can compose the skills to complete long horizon tasks. To achieve my goal, my research focuses on reinforcement learning (RL), imitation learning (IL), robotics, meta-learning, and continual learning.

I am interested in collaborating on research projects so feel free to contact me via bryan.chan@ualberta.ca.