- Leveraging Dual Process Theory in Language Agent Framework for Real-time Simultaneous Human-AI Collaboration, accepted to ACL 2025
- ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination, accepted by NeurIPS 2024 Dataset and Benchmark Track
- Order Matters: Agent-by-agent Policy Optimization, accepted by ICLR 2023
- Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts, published in IJCAI 2021
Research Experience
Involved in multiple research projects, including giving a talk about cooperative multi-agent reinforcement learning at RLChina, and publishing works in conferences such as IJCAI, ICLR, and NeurIPS.
Education
Earned his B.Eng. in Computer Science and Technology from the School of Computer Science and Engineering, Sun Yat-sen University in 2020; currently a Ph.D. candidate at Shanghai Jiao Tong University, supervised by Prof. Weinan Zhang and Prof. Ying Wen, and selected into the Wen-Tsun Wu AI Honorary Doctoral Class in 2020.
Background
Research interests include decision-making and multi-agent systems, with a specific focus on multi-agent decision-making in cooperative scenarios, especially the efficiency of cooperative multi-agent reinforcement learning, zero-shot generalization ability in cooperative multi-agent systems, and large language models for decision-making, specifically human-AI collaboration.