Short Bio

I'm a Ph.D. student in Computer Science in the Khoury College of Computer Science at Northeastern University. My advisor is Christopher Amato. Previously, I was a master in Computer Science and Data Science at Columbia University working with Sharon Di and Gail Kaiser. I got my bachelor degree in Software Engineering from Sun Yat-sen University, where I was advised by Wuhui Chen. My research interests include artificial intelligence, multi-agent system, game theory and machine learning.

My research focuses on developing data-driven decision-making methods for multi-agent systems (robots, vehicles, and humans). My research aims at: (1) developing cooperative multi-agent reinforcement learning theory to empower its downstream applications; (2) modeling societal-scale multi-agent system dynamics using game theory approaches, and providing high-quality and scalable solutions accordingly. My research has board applications in various real-world scenarios, including intelligent transportation systems and multi-robot navigation.

Keywords: Multi-Agent Reinforcement Learning; Mean-Field Game; Decentralized Partially-Observable Markov Decision Process.

Education

• Northeastern University, Boston, Massachusetts
  Ph.D. in Computer Science, 2024 - Present
  
• Columbia University, New York, New York
  M.S. in Computer Science, Data Science, 2021 - 2024
  
• Sun Yat-sen University, Guangzhou, Guangdong, China
  B.E. in Software Engineering, 2016 - 2020
  

Featured Papers

• [Mathematics]  Scalable Learning for Spatiotemporal Mean-Field Games using Physics-Informed Neural Operator.
  Shuo Liu, Xu Chen, Sharon Di,
  in Mathematics, 2024.
     

• [ECAI]  Learning Dual Mean-Field Games on Graphs.
  Xu Chen, Shuo Liu, Sharon Di,
  in 26th European Conference on Artificial Intelligence.
       

• [AAMAS]  A Hybrid Framework of Reinforcement Learning and Physics-Informed Deep Learning for Spatiotemporal Mean-Field Games.
  Xu Chen, Shuo Liu, Sharon Di,
  in 22nd International Conference on Autonomous Agents and Multiagent Systems.
       

• [ITSC]  SMART-eFlo: An Integrated SUMO-Gym Framework for Multi-Agent Reinforcement Learning in Electric Fleet Management Problem.
  Shuo Liu*, Yunhao Wang*, Xu Chen, Yongjie Fu, Sharon Di,
  in 25th IEEE International Conference on Intelligent Transportation Systems.
     

Teaching Experience

• Course Assistant, CSOR 4246 Algorithm for Data Science, Fall 2021.
• Course Assistant, COMS 4231 Analysis of Algorithms, Spring 2022.
• Course Assistant, COMS 4995 Empirical Methods for Data Science, Spring 2022, Fall 2022.