Yunli Shao

Yunli Shao, Ph.D., is an Assistant Professor at the University of Georgia's School of Electrical & Computer Engineering, Department of Electrical and Computer Engineering. His research focuses on applied control systems, e-mobility, and connected/automated vehicles, emphasizing energy efficiency, traffic optimization, and AI integration in IoT. He is affiliated with the Boyd Research and Education Center and actively publishes in areas such as vehicle dynamics, smart infrastructure, and digital twin technologies.

Shao's work explores real-time traffic prediction, cyber-physical systems integration, and eco-driving strategies for electric vehicles. His recent studies include frameworks for digital twin cities, edge computing for urban traffic management, and cooperative control strategies for connected vehicles. He has collaborated on hardware-in-the-loop testbeds and living labs to evaluate autonomous systems' efficacy and sustainability.

His research demonstrates a blend of theoretical advancements (e.g., pseudospectral optimization, algebraic approaches) and practical applications, including real-sim interfaces for cross-domain simulation and AI-driven traffic signal control. While no specific awards are listed, his prolific publication record reflects a strong academic profile in transportation engineering and control systems.