Published several papers including 'Make an Offer They Can't Refuse: Grounding Bayesian Persuasion in Real-World Dialogues without Pre-Commitment', 'Aegis: Automated Error Generation and Identification for Multi-Agent Systems', and more, with some submitted to ICLR 2025 and NeurIPS DB Track 2025.
Research Experience
Conducts research in the PAIR-Lab, focusing on AI Alignment, AI for Governance, and Multi-Agent Systems.
Education
Received B.E. degree in Computer Science and Technology from the School of Computer Science at Wuhan University in 2023; currently a third-year Ph.D. Candidate at the Institute for AI, School of Intelligence Science and Technology, Peking University, under the supervision of Prof. Yaodong Yang in the PAIR-Lab team.
Background
Research interests include AI Alignment & Governance, Game Theory & Multi-Agent System, Human-AI Interaction, and Reinforcement Learning. His long-term goal is to build a human-AI collaborative system for reforming social progress, with a particular focus on AI's capability as a social and cultural technology.