Ziyan Luo

Ziyan Luo

Ph.D. Candidate

Mila, McGill University

Biography

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.

🌟 Research Interest: RL & Abstraction

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.

🎼🏸 Beyond the Lab: Music, Sports & More

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.

Interests

  • Reinforcement Learning
  • Abstraction
  • Formal Verification

Education

  • Ph.D. in Computer Science

    Mila, McGill University

Experience

 
 
 
 
 

Ph.D. Candidate

Mila, McGill University

Sep 2021 – Present Montreal, Quebec
 
 
 
 
 

Research Intern

Microsoft Research Asia

Nov 2019 – Mar 2020 SRG, MSRA, Beijing, China

Match Plan Generation in Web Search with Parameterized Action Reinforcement Learning

  • Design DRL algorithms for Inverted Index Match Plan Generation, replacing current hand-crafted heuristics in the query process of Bing
 
 
 
 
 

Research Assistant

Tsinghua University

Mar 2019 – Jan 2021 Beijing

Spatio-temporal Trajectory Prediction

  • Supervised by Jilong Wang (chair of APAN) and Congcong Miao
  • ACN: accepted by WSDM'20 (top 7%, oral)
  • RLMob: accepted by WSDM'22

Selected Publications

Click a title to read the story behind the work; find more on Google Scholar.