报告题目：The Advances in Neurodynamic Optimization

报告人： Prof. Jun Wang，City University of Hong Kong, Hong Kong

报告地点: 西南大学电子信息工程学院 320会议室

报告时间：2025年12月26日（星期五）10:00-11:00

内容简介：

As an important tool for scientific research and engineering applications, optimization is omnipresent in a wide variety of settings. It is computationally challenging when optimization procedures must be performed in real-time to optimize the performance of dynamical systems. For such applications, classical optimization techniques may not be suitable due to the problem's dimensionality and the stringent requirement for computational time. New paradigms are needed. One very promising approach to optimization is to apply artificial neural networks. Due to the inherent nature of parallel and distributed information processing in neural networks, the convergence rate of the solution process remains constant as the problem size increases. This talk will present the state-of-the-art in neurodynamic optimization models and selected applications. Specifically, starting with the concept and motivation of neurodynamic optimization, I will review the historical background and present the state-of-the-art in neurodynamic optimization, including various individual models for convex and generalized convex optimization. Additionally, I will present a multiple-timescale neurodynamic approach to selected constrained optimization problems. In addition, I will introduce population-based collaborative neurodynamic approaches to constrained distributed and global optimization by deploying a population of individual neurodynamic models with diversified initial states at a lower level coordinated by using some global search and information exchange rules based on swarm intelligence at an upper level. Ultimately, I will demonstrate that many constrained optimization problems in science and engineering can be effectively and efficiently solved using neurodynamic optimization.

报告人简介：

Jun Wang is a chair professor of Computational Intelligence in the Department of Computer Science and the Department of Data Science at City University of Hong Kong. Prior to this position, he held various academic positions at Dalian University of Technology, Case Western Reserve University, University of North Dakota, and the Chinese University of Hong Kong. He also held various short-term visiting positions at USAF Armstrong Laboratory, RIKEN Brain Science Institute, Dalian University of Technology, Huazhong University of Science and Technology, and Shanghai Jiao Tong University. He received a B.S. degree in electrical engineering and an M.S. degree in systems engineering from Dalian University of Technology and his Ph.D. degree in systems engineering from Case Western Reserve University. His current research interests include neural networks and their applications. He published about 350 journal papers, 15 book chapters, 11 edited books, and numerous conference papers in these areas. He is the Editor-in-Chief of the IEEE Transactions on Artificial Intelligence and was the Editor-in-Chief of the IEEE Transactions on Cybernetics. He was the organizer of several international conferences, including the General Chair of the 13th International Conference on Neural Information Processing (2006) and the 2008 IEEE World Congress on Computational Intelligence, as well as the Program Chair of the IEEE International Conference on Systems, Man, and Cybernetics (2012). He is an IEEE Fellow, IAPR Fellow, CAAI Fellow, a Fellow of the Hong Kong Academy of Engineering, a foreign member of Academia Europaea, and an IEEE Systems, Man and Cybernetics Society Distinguished Lecturer (2017-2018), and was an IEEE Computational Intelligence Society Distinguished Lecturer (2010-2012, 2014-2016). In addition, he served as President of Asia Pacific Neural Network Assembly (APNNA) in 2006 and many organizations such as IEEE Fellow Committee; IEEE Computational Intelligence Society Awards Committee; IEEE Systems, Man, and Cybernetics Society Board of Governors,   He is a recipient of an IEEE Transactions on Neural Networks Outstanding Paper Award and APNNA Outstanding Achievement Award in 2011, Neural Networks Pioneer Award from IEEE Computational Intelligence Society in 2014, CAAI Wu Wenjun AI Science & Technology Achievement Award in 2016, and Norbert Wiener Award from IEEE Systems, Man and Cybernetics Society in 2019, among others.