Jing Sun

Jing Sun received her Ph. D degree from the University of Southern California in 1989, and her B. S. and M. S. degrees from the University of Science and Technology of China in 1982 and 1984 respectively, all in Electrical Engineering.

From 1989-1993, she was on the faculty of the Electrical and Computer Engineering Department, Wayne State University. She joined Ford Research Laboratory in 1993 where she worked in the Powertrain Control Systems Department on engine emission control and fuel economy optimization projects. After spending almost 10 years in industry, she came back to academia and joined the Naval Architecture and Marine Engineering Department and Electrical Engineering and Computer Science Department at the University of Michigan in September 2003, where she holds the title of Michael G. Parsons Collegiate Professor of Engineering now. Her research interests include control theory and optimization, as well as their applications to marine and automotive propulsion systems.

She holds 39 US patents, has co-authored a textbook, Robust Adaptive Control (Prentice Hall, 1996), and published over 200 journal and conference papers. She has served as associate editor for several control journals, including the IEEE Transactions on Automatic Control, IEEE Transactions on Control Systems Technology, and International Journal of Adaptive Control and Signal Process. She is an IEEE fellow and one of the three recipients of the 2003 IEEE Control System Technology Award.

Her research Interests include: Control system development and optimization for marine and automotive propulsion systems, with focus on system modeling, identification, control algorithm development and integration, control system rapid prototyping and experimental validation. Modeling, control and optimization of electrified vehicles, with emphasis on transient energy management for mobile applications.
Adaptive control theory, with focus on algorithm and tool development aiming at improved transient performance and convergence properties. Advanced control methodologies, including optimal control and nonlinear control, and their real-time applications to marine and automotive systems.