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 undergraduate studies at Sun Yat-sen University, both in CS.

My research focuses on multi-agent reinforcement learning, multi-agent systems, and decentralization. Specifically: (1) Optimizing the 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; Large Language Models; Decentralization.

Selected Papers

• [ICML-26]  Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic.
  Shuo Liu, Tianle Chen, Ryan Amiri, Christopher Amato.
  In Proceedings of the 43rd International Conference on Machine Learning.
         

• [AAAI-26]  LLM Collaboration with Multi-Agent Reinforcement Learning.
  Shuo Liu, Zeyu Liang, Xueguang Lyu, Christopher Amato.
  In Proceedings of the 40th Annual AAAI Conference on Artificial Intelligence.
         

• [RLC-26]  Fixing Incomplete Value Function Decomposition for Multi-Agent Reinforcement Learning.
  Andrea Baisero, Rupali Bhati, Shuo Liu, Aathira Pillai, Christopher Amato.
  In Proceedings of the 3rd Reinforcement Learning Conference.
   

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: ICML (2026); AAMAS (2026); AAAI (2026); RLC(2026); ICRA (2026); IJCNN (2025, 2026).