I am a Ph.D. student at the University of Connecticut. My current research interests include uncertainty quantification, perception, deep learning, and reinforcement learning.

I received a bachelor’s degree in automation from Nanjing University, Nanjing, China, in 2016, and a master’s degree in electronic science and technology from Shanghai Jiao Tong University, Shanghai, China, in 2019. After graduation, I worked as a full-time software engineer in Shanghai Huawei Technologies Company, China, from 2019 to 2021. I joined UConn as a Ph.D. student in computer science and engineering starting in Autumn 2021.

News

• [2024/1] Our paper “Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation” is accepted by IEEE Robotics and Automation Letters. It is available on arxiv, website.
• [2024/1] Our paper “What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?” is accepted by Transactions on Machine Learning Research.
• [2023/11] Our paper “ViTAL: Vision Transformer-Assisted Active Testing for Label-Efficient Evaluation of Complex Vision Tasks” is submitted to CVPR 2024.
• [2023/8] Completed the research internship at Bosch, Sunnyvale, CA, USA. Express my heartfelt gratitude to my manager, mentor and all colleagues.
• [2023/5] Our paper “Robust Multi-Agent Reinforcement Learning with State Uncertainty” is accepted by Transactions on Machine Learning Research.
• [2023/5] Exciting to receive the Synchrony Financial Cybersecurity Graduate Fellowship and the Predoctoral Fellowship from UCONN.
• [2023/1] Our paper “Uncertainty Quantification of Collaborative Detection for Self-Driving” is accepted by ICRA 2023 website. See you at London.
• [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), Philadelphia, USA, May 2022.