Zhong-Ping Jiang stands as a preeminent figure in the field of control theory and systems engineering, currently holding the distinguished position of Institute Professor in the Department of Electrical and Computer Engineering at New York University's Tandon School of Engineering. He earned his B.Sc. in mathematics from Wuhan University in 1988, followed by an M.Sc. in statistics from the University of Paris XI in 1989, and completed his Ph.D. in automatic control and mathematics from ParisTech-Mines in 1993 under the guidance of Professor Laurent Praly. His academic journey progressed from Assistant Professor at Polytechnic University in 1999 through Associate Professor to his current position as Full Professor since 2007, demonstrating a sustained trajectory of scholarly excellence and leadership. Jiang has established himself as a pillar of the global control systems community, with his research program consistently addressing fundamental challenges in nonlinear dynamics and control theory. His early career included research fellowships at The Australian National University and Sydney University, followed by a visiting position at UC Riverside, which laid the foundation for his groundbreaking theoretical contributions.
Professor Jiang is internationally renowned for his fundamental contributions to stability and control of interconnected nonlinear systems, particularly as a key developer of the nonlinear small-gain theory that has become foundational in modern control systems analysis. His research has yielded significant theoretical advances in robust adaptive dynamic programming, distributed nonlinear control, and model-based learning approaches that have transformed how engineers approach complex system design. With multiple influential books including "Nonlinear Control Under Information Constraints" and "Robust Event-Triggered Control of Nonlinear Systems," his work bridges theoretical rigor with practical applications across diverse domains. His research has achieved remarkable impact, evidenced by his recognition as one of Stanford's Top 2% Most Highly Cited Scientists in 2023 and his consistent inclusion among Clarivate Analytics' Highly Cited Researchers. These contributions have enabled critical advances in systems where stability and control of interconnected components present significant theoretical and practical challenges.
Beyond his research contributions, Professor Jiang has significantly shaped the field through his editorial leadership as Deputy Editor-in-Chief of the Journal of Control and Decision and through numerous best paper awards at major international conferences. His work continues to evolve toward cutting-edge applications in computational neuroscience, connected and autonomous vehicles, and cyber-physical systems, where his theoretical frameworks enable new capabilities in real-world implementations. As a dedicated mentor, he has guided numerous graduate students and postdoctoral researchers who have gone on to establish their own successful careers in academia and industry, extending his intellectual legacy. Professor Jiang's election to prestigious academies including the European Academy of Sciences and Arts in 2023 and Academia Europaea in 2021 underscores the broad recognition of his scholarly impact. His ongoing exploration of learning-based control for network systems promises to further advance the integration of classical control theory with modern machine learning approaches, cementing his legacy as a visionary in the field of control engineering.
