Summary
Albert Zhan is a PhD student at Mila with 11 years of experience focused on reinforcement learning, building on a strong academic foundation from UC Berkeley (BS CS, 4.0). His research spans private RL and robot learning, including work advised by Pieter Abbeel and a paper presented at the NeurIPS 2019 Deep RL workshop. He has taught core CS topics (Discrete Math and Probability) as a UGSI at Berkeley, demonstrating an ability to translate theory into clear instruction. Earlier leadership organizing a large high-school ML hackathon and math research at Tournament of Towns reflect a long-standing blend of mentorship, community-building, and mathematical depth. Now based in Canada, he combines rigorous theoretical training with applied RL research at a top AI institute.
11 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Mila - Quebec Artificial Intelligence Institute
Bachelor's degree, Computer Science, 4.0, Bachelor's degree, Computer Science, 4.0 at University of California, Berkeley
Vincent Massey
French, English, Chinese