Hi there! I’m Ziyan “Ray” Luo, a Ph.D. candidate at Mila, McGill, fortunate to work with (and learn from) Dr. Xujie Si, Dr. Doina Precup, and my talented colleagues, who continuously inspire me.
I am broadly interested in conceptually challenging problems in Reinforcement Learning (RL). A central theme of my research is the study of abstraction in RL, which provides principles for developing efficient, scalable, and generalizable agents.
Inspired by early research in formal verification, which leveraged abstraction to manage complexity, I investigate a range of abstraction mechanisms, such as state abstraction for representation learning, and temporal abstractions in hierarchical RL, to integrate formal structure with learning-based flexibility, guided by the formal methods community’s emphasis on precision, scientific rigor, and long-term research impact.
When I’m not exploring algorithms, you may find me composing music that tells stories. Here’s my portfolio. Some tracks were even featured in popular video games! I love blending electronic sounds with acoustic instruments to create immersive, story-telling pieces. Glad that they are well-received: now, I have over 10K followers in multiple Chinese music distribution platforms and social media!
Ball sports keep me energized: badminton, tennis, table tennis, billiards—you name it! And if you’re an animal lover, check out my Instagram for some furry friends.
Ph.D. in Computer Science
Mila, McGill University
Work with Dr. Xujie Si in “REAP” group, and Dr. Doina Precup in Reasoning and Learning Lab
TA for Reinforcement Learning (by Doina Precup, Isabeau Prémont-Schwarz, Nishanth Anand); Winter 2024, recipient of McGill TA Award (awarded to 4 TAs annually in CS department); Winter 2026, as head TA.
Reviewer - CAV'24 (and Volunteer), NeurIPS'24, TMLR, NeurIPS'23 MathAI workshop
Match Plan Generation in Web Search with Parameterized Action Reinforcement Learning
Spatio-temporal Trajectory Prediction
Click a title to read the story behind the work; find more on Google Scholar.