Zun Li

Email: lizun [at] umich [dot] edu

I am a research engineer at Google DeepMind.

I have earned my Ph.D. in Computer Science on Jan. 2024 at University of Michigan. My Ph.D. advisor is Prof. Michael P. Wellman.

Education

University of Michigan, U.S., from Sep. 2018 to Jan. 2024
Ph.D. Student in Computer Science and Engineering

Shanghai Jiao Tong University, China, from Sep. 2014 to Jun. 2018
B.S.E. in Computer Science (IEEE Honored Class)

Interests

I aspire to study intelligence through multi-agent lens. I have worked on computational game theory, (deep) multi-agent planning / learning, agent-based simulation methods, auctions, and data markets.

Selected Papers

• "A Meta-Game Evaluation Framework for Deep Multiagent Reinforcement Learning"[arxiv]
Zun Li, Michael P. Wellman
In Proceedings of Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI), 2024.
Best Paper Award of Adaptive and Learning Agents (ALA) Workshop at AAMAS, 2024.
Keywords: Meta-Strategies / Meta-Game Analysis, Evaluation, Bootstrapping Statistics, Empirical Game-Theoretic Analysis, Search

• "Search-Improved Game-Theoretic Multiagent Reinforcement Learning in General and Negotiation Games (Extended Abstract)"[arXiv]
Zun Li, Marc Lanctot, Kevin McKee, Luke Marris, Ian Gemp, Daniel Hennes, Paul Muller, Kate Larson, Yoram Bachrach, Michael P. Wellman
In Proceedings of Twenty-Second International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2023.
Keywords: Extensive-Form Games, Nash Bargaining Solutions, Game-Tree Search, Population-Based Reinforcement Learning, Negotiation

• "Evolution Strategies for Approximate Solution of Bayesian Games"[PDF][TALK][SLIDES][POSTER]
Zun Li, Michael P. Wellman
In Proceedings of Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021.
Keywords: Bayesian Games, Equilibrium Computation, Deep Learning, Evolutionary Computation, Auctions

• "Structure Learning for Approximate Solution of Many-Player Games" [PDF][SLIDES][POSTER]
Zun Li, Michael P. Wellman
In Proceedings of Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020.
Keywords: Normal-Form Games, Equilibrium Computation, Machine Learning, Graphical Models

Working Experience

Google DeepMind, Research Engineer, New York, Feb. 2024-Now
DeepMind Alberta, Research Scientist Intern, Edmonton, Jun. 2022-Nov. 2022
Google Inc., Software Engineering Intern, Core Google Display Ad Team, Remote, Jun. 2021-Aug. 2021


This guy designed this neat webpage.