Gang Tao

Gang Tao is a Professor in the Department of Electrical and Computer Engineering at the University of Virginia, where he has worked for over 30 years in adaptive control theory and applications. He holds a Ph.D. in Electrical Engineering from the University of Southern California and serves as an IEEE Fellow. His research focuses on adaptive control of complex systems with actuator/sensor nonlinearities, stability analysis, and control of systems with uncertain faults.

• Education: B.S. (1982) University of Science and Technology of China; M.S. degrees (1984-1989) and Ph.D. (1989) from University of Southern California.

Research Interests: His work spans adaptive control, fault-tolerant systems, robotics, and intelligent learning, addressing challenges in multivariable systems, structural damage compensation, and resilient control for high-speed trains, aircraft, and renewable energy systems.

Publication Trends: Recent articles emphasize Koopman operator-based optimal control for multi-robot systems, adaptive backstepping techniques, and fault accommodation in aerospace and transportation applications. His work integrates machine learning with classical control theory for dynamic mutation handling.

Scientific Recognition:

• IEEE Fellow
• Extensive editorial roles in leading journals
• Conference organization and plenary speaking

Teaching Contributions: He has taught foundational courses including Adaptive Control, Linear Control Systems, and advanced topics in robotics and optimal control. His educational materials reflect deep technical expertise and pedagogical innovation.