Data Driven Learning and Control seminar series is organized by the Information and Decision Science Lab at Cornell University and aims to explore the latest advancements and interdisciplinary approaches to data-driven learning and control systems.
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Bio: Zhong-Ping Jiang is widely recognized for his pioneering contributions to the stability and control of interconnected nonlinear systems and as a leading contributor to nonlinear small-gain theory. He is currently an institute professor in the Department of Electrical and Computer Engineering at the New York University Tandon School of Engineering. His research interests include stability theory, robust, adaptive, and distributed nonlinear control, robust adaptive dynamic programming, reinforcement learning, and their applications to information, mechanical, transportation, and biological systems.
Jiang serves on the Board of Governors of the IEEE Intelligent Transportation Systems Society and leads its Distinguished Lecturer Program. He has also served as Deputy Editor-in-Chief, Senior Editor, and Associate Editor for numerous leading journals, such as IEEE Transactions on Automatic Control, Mathematics of Control, Signals and Systems, and Systems & Control Letters. He has been recognized as a Clarivate Highly Cited Researcher and is listed among Stanford University’s Top 2% Most-Cited Scientists. In 2022, he received the Excellence in Research Award from the NYU Tandon School of Engineering.
Jiang is a Foreign Member of Academia Europaea (the Academy of Europe) and a Member of the European Academy of Sciences and Arts. He is also a Fellow of the IEEE, IFAC, CAA, AAIA, and AAAS.