Advances in Collaborative Neurodynamic Optimization

Guest Lecture by Professor Jun Wang

Prof. Jun Wang

Abstract:

Pioneered by Nobel Laureate John Hopfield, neurodynamic optimization has grown over the past four decades into a powerful method for solving complex optimization problems. Its strength lies in its biologically inspired approach and ability to process information in parallel and distributed ways. This talk will highlight recent advances in neurodynamic optimization, focusing on a collaborative framework where multiple models start from different points to explore diverse solutions. A swarm intelligence-based rule is used to help models escape local traps and move toward better, global solutions. Real-world examples will showcase how this approach can be applied to machine learning, managing chiller systems, and optimizing financial portfolios.

Speakers Biography:

Professor Jun Wang is a Chair Professor at City University of Hong Kong. He has held academic positions at Dalian University of Technology, Case Western Reserve University, the University of North Dakota, and the Chinese University of Hong Kong, as well as short-term visiting roles at institutions including USAF Armstrong Laboratory, RIKEN Brain Science Institute, and Shanghai Jiao Tong University. He currently serves as Editor-in-Chief of IEEE Transactions on Artificial Intelligence and previously held the same role for IEEE Transactions on Cybernetics. A distinguished IEEE Life Fellow, he is also a Fellow of the International Association for Pattern Recognition, the Hong Kong Academy of Engineering, and a foreign member of Academia Europaea. His honors include the APNNA Outstanding Achievement Award, IEEE CIS Neural Networks Pioneer Award, CAAI Wu Wenjun AI Achievement Award, and IEEE SMCS Norbert Wiener Award, among others.