Contact Information
Office: 3029-B SERC
E-Mail: sli@eng.ua.edu
Phone: (205) 348-9085
Fax: (205) 348-6959

Center for Advanced Vehicle Technologies
Electrical and Computer Engineering

Dr. Shuhui Li (Senior Member, IEEE) received the B.S. and M.S. degrees in electrical engineering from Southwest Jiaotong University, Chengdu, China, in 1983 and 1988, respectively, and the Ph.D. degree in electrical engineering from Texas Tech University, Lubbock, TX, USA, in 1999.,From 1988 to 1995, he was with the School of Electrical Engineering, Southwest Jiaotong University, where his fields of research interest included electrified railways, power electronics, power systems, and power system harmonics. From 1995 to 1999, he was engaged in research on wind power, artificial neural networks, and applications of massive parallel processing. He joined Texas A&M University, Kingsville, TX, USA, as an Assistant Professor, in 1999, and an Associate Professor in 2003. He joined the University of Alabama (UA), Tuscaloosa, AL, USA, in 2006 and is currently a full professor at UA. He is a Voting Member of the IEEE 2800, P2030, 2418.5, and P2030.12 working groups, involving the IEEE standardization works on Interconnection and Interoperability of Inverter-Based Resources, Smart Grid Interoperability, Blockchain in Energy, and Microgrid Protection Systems. He is recipient of the IEEE Standards Association’s Emerging Technology Award for his contribution to IEEE Std. 2800-2022. His current research interests include renewable energy systems, power electronics, power systems, electric machines and drives, and applications of artificial intelligence and machine learning in power and energy systems. Dr. Li is a senior member of IEEE and a senior member of National Academy of Inventors.

Ph.D. Texas Tech University
M.S. Southwest Jiaotong University
B.S. Southwest Jiaotong University, (Chengdu, China) 

Research Specialties

• Renewable Energy Systems
• Power Electronics, Electric Machines and Drives, Power Systems
• Artificial Intelligence and Neural Networks 
• Modeling, Analysis, and Control of Dynamic Systems 
• Smart Homes and Buildings 
• Massively Parallel Processing Applications 
• Software Engineering
• Measurements and Instrumentation