Yudong Luo Department of Decision Science HEC Montreal & Mila - Quebec AI Institute E-mail: yudong [dot] luo [at] hec [dot] ca [Google Scholar]

About

My research interests lie at the intersection of reinforcement learning, risk management, and machine learning.
Currently work as a postdoctoral researcher with Professor Erick Delage.

Publication

* equal contribution, † corresponding

Work in progress

• Measures of Variability for Risk-averse Policy Gradient
  Yudong Luo, Yangchen Pan, Jiaqi Tan, Pascal Poupart
  [arXiv]

Refereed

• Reevaluation of Large Neighborhood Search for MAPF: Findings and Opportunities
  Jiaqi Tan*, Yudong Luo*, Jiaoyang Li, Hang Ma
  International Symposium on Combinatorial Search (SoCS), 2025
  [arXiv] [Code]
• A Simple Mixture Policy Parameterization for Improving Sample Efficiency of CVaR Optimization
  Yudong Luo, Yangchen Pan, Han Wang, Philip Torr, Pascal Poupart
  Reinforcement Learning Conference (RLC), 2024
  [PDF] [Code]
• Risk, Reward, and Reinforcement Learning in Hockey Analytics
  Sheng Xu, Oliver Schulte, Yudong Luo, Pascal Poupart, Guiliang Liu
  Book chapter of Artificial Intelligence and Machine Learning in Sports Science
  [PDF]
• An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient
  Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan
  Conference on Neural Information Processing Systems (NeurIPS), 2023
  [PDF] [Slides] [Code in supplementary]
• Benchmarking Constraint Inference in Inverse Reinforcement Learning
  Guiliang Liu, Yudong Luo, Ashish Gaurav, Kasra Rezaee, Pascal Poupart
  International Conference on Learning Representations (ICLR), 2023
  [PDF] [Code]
• Uncertainty-Aware Reinforcement Learning for Risk-Sensitive Player Evaluation in Sports Game
  Guiliang Liu, Yudong Luo, Oliver Schulte, Pascal Poupart
  Conference on Neural Information Processing Systems (NeurIPS), 2022
  [PDF] [Slides]
• Distributional Reinforcement Learning with Monotonic Splines
  Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart
  International Conference on Learning Representations (ICLR), 2022
  [PDF] [Poster] [Code in supplementary]
• Learning Selective Communication for Multi-Agent Path Finding
  Ziyuan Ma*, Yudong Luo* †, Jia Pan
  IEEE Robotics and Automation Letters (RA-L), and ICRA, 2022
  [arXiv] [Code] [Demo] [Video]
• Leveraging Approximate Constraints for Localized Data Error Detection
  Mohan Zhang, Oliver Schulte, Yudong Luo
  Intl Workshop on Exploiting Artificial Intelligence Techniques for Data Management (aiDM@SIGMOD), 2021
  [PDF]
• Distributed Heuristic Multi-Agent Path Finding with Communication
  Ziyuan Ma*, Yudong Luo*, Hang Ma
  IEEE International Conference on Robotics and Automation (ICRA), 2021
  [PDF] [Code] [Demo] [Slides]
• Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players
  Yudong Luo, Oliver Schulte, Pascal Poupart
  International Joint Conference on Artificial Intelligence (IJCAI), 2020
  [PDF] [Slides] [Poster] [Code] [Video]
• Valuing Sports Actions and Players with Inverse Reinforcement Learning
  Yudong Luo and Oliver Schulte
  AAAI workshop, Artificial Intelligence in Team Sports (AITS@AAAI), 2020 (spotlight)
  [PDF] [Slides]
• Deep soccer analytics: Learning an action-value function for evaluating soccer players
  Guiliang Liu, Yudong Luo †, Oliver Schulte, Tarak Kharrat
  Data Mining and Knowledge Discovery (DMKD), 2020 (ECML Journal Track)
  [PDF] [Slides]
• EEG-based Emotion Recognition using Domain Adaptation Network
  Yi-Ming Jin, Yu-Dong Luo, Wei-Long Zheng, Bao-Liang Lu
  International Conference on Orange Technologies (ICOT), 2017 (invited paper)
  [PDF] [Slides]

Education

• PhD. Computer Science, University of Waterloo, affiliate with Vector Institute, Canada, 2020 - 2024
  → with Professor Pascal Poupart
  Thesis: Policy Learning under Uncertainty and Risk [PDF]
• MSc. Computing Science (Thesis-based), Simon Fraser University, Canada, 2018 - 2020
  → with Professor Oliver Schulte, also work with Professor Hang Ma
  Thesis: Inverse Reinforcement Learning for Team Sports [PDF]
• BEng. Computer Science, Shanghai Jiao Tong University, China, 2014 - 2018
  → work with Professor Bao-Liang Lu

Experience

• The Chinese University of HongKong (Shenzhen), Shenzhen, China. Visiting Researcher. Jan. 2025 - Apr. 2025
• University of Waterloo, Waterloo, Canada. Visiting Researcher. Sep. 2024 - Dec. 2024
• Noah's Ark Laboratory, Toronto, Canada. Intern. Jul. 2022 - Dec. 2022
• SportLogiq, Vancouver area, Canada. Mitacs Accelerate Program Intern. Mar. 2020 - Jun. 2020
• National University of Singapore, School of Computing. Visiting Researcher. Jul. 2017 - Sep. 2017

Talk

• Measures of Variability for Risk-averse Policy Gradient, Optimization Day, HEC Montreal, May 2025, [Slides]
• Multi-Agent Reinforcement Learning for MAPF, Guest Lecture, Simon Fraser University, Mar. 2025 (online), [Slides]
• An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient, Vector Institute, Nov. 2023 (online), [Slides]
• Mean-Variance Reinforcement Learning, UWaterloo, Dept. of Actuarial Science, Mar. 2023, [Slides]
• Risk-Sensitive Player Evaluation in Sports Game, ETHz, Jan. 2023 (online), [Slides]
• Multi-Agent Path Finding with Deep RL and Communication, USC, Nov. 2022 (online), [Slides]

Service

• Reviewer: AAMAS 2022; ICRA 2022, 2024, 2025; NeurIPS 2022 - 2025; ICLR 2024, 2025; ICML 2024; RLC 2024, 2025

Miscellaneous

• Gallery: [Photos]
• Guitar: [Covers]
• Tool: [Mō Yú]
• Erdős number: [3]
• And

Acknowledgement

My research has been supported by

• the Vector Institute Research (21-24)
• Ontario Graduate Scholarship, by Ontario province (23)
• President’s Graduate Scholarship, by UWaterloo (23)
• David R. Cheriton Graduate Scholarship, by School of CS, UWaterloo (23, 24)
• Waterloo AI Institute Graduate Scholarship, by Waterloo.AI [Link] (24)
• Postdoctoral research scholarship, by Fonds de recherche Québec Nature et technologies (FRQNT) (25-27)

© YD | Last update: Apr 2025