I am currently a final-year Ph.D. candidate in computer science and engineering working on artificial intelligence supervised by Prof. Fei Miao at the University of Connecticut. I was working on game theoretic energy management approaches in Dynamic Systems Control Lab at the University of Michigan-Shanghai Jiao Tong University Joint Institute supervised by Prof. Chengbin Ma.
My current research interests include robust and scalable multi-agent reinforcement learning, artificial intelligence, deep learning, autonomous driving, computer vision, and game theory.
- [2023/2] Our paper “Shared Information-Based Safe And Efficient Behavior Planning For Connected Autonomous Vehicles” gets the Best Paper Award in the DCAA workshop at AAAI 2023, Washington, DC. Available on arxiv.
- [2023/1] Our paper “What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?” is available on arxiv, website.
- [2023/1] Our paper “Uncertainty Quantification of Collaborative Detection for Self-Driving” is accepted by the 2023 IEEE International Conference on Robotics and Automation (ICRA), available on arxiv, website.
- [2023/1] Our paper “Spatial-Temporal-Aware Safe Multi-Agent Reinforcement Learning of Connected Autonomous Vehicles in Challenging Scenarios” is accepted by the 2023 IEEE International Conference on Robotics and Automation (ICRA), available on arxiv.
- [2022/9] Our paper “A Multi-Agent Reinforcement Learning Approach For Safe and Efficient Behavior Planning Of Connected Autonomous Vehicles” is available on arxiv, website.
- [2022/8] I get the General Electric (GE) fellowship of excellence. The GE Fellowship for Excellence program is established to recognize excellence of current graduate students and to facilitate their completion of the Ph.D. program.
- [2022/7] Our paper “Towards Safe Autonomy in Hybrid Traffic: The Power of Information Sharing in Detecting Abnormal Human Drivers Behaviors” is presented in the AI4TS workshop at the 31st International Joint Conference On Artificial Intelligence (IJCAI 2022).
- [2022/7] Our paper “DeResolver: A Decentralized Negotiation and Conflict Resolution Framework for Smart City Services” is accepted by ACM Transactions on Cyber-Physical Systems. (available online).
- [2022/5] Our paper “Stable and Efficient Shapley Value-Based Reward Reallocation for Multi-Agent Reinforcement Learning of Autonomous Vehicles” is presented on the 2022 IEEE International Conference on Robotics and Automation (ICRA), available online.