Dr. Chenglong Gong is a Postdoctoral Researcher and Assistant Researcher at the School of Automation, Wuhan University of Technology, China. He received the Ph.D. degree in Traffic Information Engineering and Control from Wuhan University of Technology in 2023 and is currently conducting postdoctoral research in Information and Communication Engineering.
His research focuses on automation, artificial intelligence–enabled control, and advanced control theory, with an emphasis on autonomous and marine systems. He has published multiple peer-reviewed journal articles in leading international journals, including Ocean Engineering, IEEE Transactions on Circuits and Systems II: Express Briefs, Advanced Theory and Simulations, and Journal of Marine Science and Engineering.
Dr. Gong has led and participated in several national, provincial, and industry-funded research projects, gaining solid experience in both theoretical control design and engineering-oriented automation applications. His current work aims to bridge intelligent algorithms, control theory, and practical automation technologies for next-generation autonomous systems.
Dr. Chenglong Gong is a Postdoctoral Researcher and Assistant Researcher at the School of Automation, Wuhan University of Technology, China. He received the Ph.D. degree in Traffic Information Engineering and Control from Wuhan University of Technology in 2023 and is currently conducting postdoctoral research in Information and Communication Engineering.
His research focuses on automation, artificial intelligence–enabled control, and advanced control theory, with an emphasis on autonomous and marine systems. He has published multiple peer-reviewed journal articles in leading international journals, including Ocean Engineering, IEEE Transactions on Circuits and Systems II: Express Briefs, Advanced Theory and Simulations, and Journal of Marine Science and Engineering.
Dr. Gong has led and participated in several national, provincial, and industry-funded research projects, gaining solid experience in both theoretical control design and engineering-oriented automation applications. His current work aims to bridge intelligent algorithms, control theory, and practical automation technologies for next-generation autonomous systems.