Short Bio

I am a Ph.D. student at the Khoury College of Computer Sciences at Northeastern University, advised by Christopher Amato. I finished my master’s at Columbia University and my undergraduate studies at Sun Yat-sen University.

My research focuses on multi-agent reinforcement learning, multi-agent systems, and decentralization. Specifically: (1) Optimizing the decentralized LLM collaboration with MARL (CoMLRL); (2) Advancing theory and algorithms for decentralized decision-making in partially observable domains (Dec-POMDP); (3) Developing game-theory approaches for multi-agent planning in societal-scale systems.

Keywords: Multi-Agent Reinforcement Learning; Multi-Agent Systems; Decentralization; Game Theory.

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
  B.E. in Software Engineering, 2016 - 2020
  

Selected Papers

• [AAAI]  LLM Collaboration with Multi-Agent Reinforcement Learning.
  Shuo Liu, Zeyu Liang, Xueguang Lyu, Christopher Amato,
  in 40th Annual AAAI Conference on Artificial Intelligence.
         

• [Mathematics]  Scalable Learning for Spatiotemporal Mean-Field Games using Physics-Informed Neural Operator.
  Shuo Liu, Xu Chen, Sharon Di,
  in Mathematics.
  Nominated as an editor's choice article!
       

Teaching

• Teaching Assistant: Northeastern CS 5180 Reinforcement Learning and Sequential Decision Making, Spring 2025.
• Course Assistant: Columbia COMS 4995 Empirical Methods for Data Science, Spring 2022, Fall 2022.
• Course Assistant: Columbia COMS 4231 Analysis of Algorithms, Spring 2022.
• Course Assistant: Columbia CSOR 4246 Algorithm for Data Science, Fall 2021.

Service

• Conference Reviewer: AAAI (2026); AAMAS (2026); ICRA (2026); IJCNN (2025, 2026).