About Me
I am a Postdoctoral Research Fellow in Prof. Ziyou Song’s research group at the University of Michigan, Ann Arbor. My research focuses on data-driven control, predictive optimization, and energy/battery-aware management for electrified and intelligent transportation systems.
My work aims to develop reliable and efficient control and optimization methods for complex dynamical systems by integrating data, partial physical knowledge, and uncertainty quantification. My current research interests include data-enabled predictive control, data informativity, uncertainty-aware learning and testing, battery degradation-aware optimization, and energy/thermal management for electric vehicles.
Before joining the University of Michigan, I received my Ph.D. in Mechanical Engineering from the National University of Singapore. I also received my B.E. and M.E. degrees in Automotive Engineering from Chongqing University.
Research Interests
- Data-driven and data-enabled predictive control
- Data informativity and uncertainty quantification
- Physics-informed learning/control
- Battery degradation-aware energy and thermal management
- Eco-driving and control of connected and automated vehicles
- Electrified transportation and energy systems
Recent News
August 2026: Received the 2025-2026 Award for Outstanding Study Elite from the China Scholarship Council (CSC), awarded to 650 Category-A recipients worldwide annually.
June 2026: Presented our paper, “Lane Change Trajectory Planning for Personalized Driving Comfort and Mobility Efficiency,” at the IEEE Intelligent Vehicles Symposium (IV) in Detroit.
May 2026: Presented our paper, “Direct Data-driven Predictive Control: A Computationally Efficient Alternative to DeePC for Eco-driving in Mixed Traffic Flows,” at the American Control Conference.
October 2025: Led the Energy Storage Lab team to win the 1st Place Award in the IEEE VTS Motor Vehicles Challenge 2025 on “Energy Management and Control of a Marine Electric Propulsion System.” Our award-winning solution was presented at the IEEE VPPC 2025 Motor Vehicles Challenge special session. [News]