The State of the Art of Neurodynamic Optimization - Past, Present, and Prospect

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IEEE Canadian Atlantic Section CIS/SMC Joint Chapter is pleased to present a Distinguished Lecturer talk from Dr. Jun Wang, Chair Professor of Computational Intelligence in the Department of Computer Science in the College of Science and Engineering at City University of Hong Kong. This talk is part of Dr. Wang's Distinguished Lecturer tour through Canada.

The talk is co-hosted by the Division of Engineering at Saint Mary's University. Refreshments and snacks will be served.



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  • 923 Robie Street
  • Halifax, Nova Scotia
  • Canada B3H 3C3
  • Building: Sobey Building
  • Room Number: SB 255
  • Click here for Map

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  • Campus map (pdf):

    https://www.smu.ca/documents/campus-map.pdf

  • Co-sponsored by IEEE Canadian Atlantic Section Computational Intelligence Society and Systems, Man and Cybernetics Society (CIS/SMC) Joint Chapter and Saint Mary's University
  • Registration closed


  Speakers

Dr. Jun Wang
Dr. Jun Wang of City University of Hong Kong

Topic:

The State of the Art of Neurodynamic Optimization - Past, Present, and Prospect

As an important tool for science research and engineering applications, optimization is  omnipresent in a wide variety of settings. It is computationally challenging when optimization procedures have to be performed in real time to optimize the performance of dynamical systems. For such applications, classical optimization techniques may not be competent due to the problem dimensionality and stringent requirement on computational time. New paradigms are needed. One very promising approach to dynamic optimization is to apply artificial neural networks. Because of the inherent nature of parallel and distributed information processing in neural networks, the convergence rate of the solution process is not decreasing as the size of the problem increases. This talk will present the state of the art of neurodynamic optimization models and selected applications. Specifically, starting from the motivation of neurodynamic optimization, we will review various recurrent neural network models for optimization. Theoretical results about the stability and optimality of the neurodynamic optimization models will be given along with illustrative examples and simulation results. It will be shown that many computational problems can be readily solved by using the neurodynamic optimization approaches.

Biography:

Jun Wang is a Chair Professor of Computational Intelligence in the Department of Computer 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 Chinese University of Hong Kong. He also held various part-time visiting positions at US Air Force Armstrong Laboratory, RIKEN Brain Science Institute, Huazhong University of Science and Technology, Dalian University of Technology, and Shanghai Jiao Tong University as a Changjiang Chair Professor. He received a B.S. degree in electrical engineering and an M.S. degree in systems engineering from Dalian University of Technology, Dalian, China. He received his Ph.D. degree in systems engineering from Case Western Reserve University, Cleveland, Ohio, USA. His current research interests include neural networks and their applications. He published about 200 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 Cybernetics. He also served as an Associate Editor of the IEEE Transactions on Neural Networks (1999-2009), IEEE Transactions on Cybernetics and its predecessor (2003-2013), and IEEE Transactions on Systems, Man, and Cybernetics – Part C (2002–2005), as a member of the editorial advisory board of International Journal of Neural Systems (2006-2013), and a member of the editorial board of Neural Networks (2012-2014) as a guest editor of special issues of European Journal of Operational Research (1996), International Journal of Neural Systems (2007), Neurocomputing (2008, 2014, 2016), and International Journal of Fuzzy Systems (2010, 2011). He was an organizer of several international conferences such as the General Chair of the 13th International Conference on Neural Information Processing (2006) and the 2008 IEEE World Congress on Computational Intelligence, and a Program Chair of the IEEE International Conference on Systems, Man, and Cybernetics (2012). He has been 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 (2011-2012); IEEE Computational Intelligence Society Awards Committee (2008, 2012, 2014), IEEE Systems, Man, and Cybernetics Society Board of Directors (2013-2015), He is an IEEE Fellow, IAPR Fellow, and a recipient of an IEEE Transactions on Neural Networks Outstanding Paper Award and APNNA Outstanding Achievement Award in 2011, Natural Science Awards from Shanghai Municipal Government (2009) and Ministry of Education of China (2011), and Neural Networks Pioneer Award from IEEE Computational Intelligence Society (2014), among others.

Email:

Address:Tat Chee Avenue, Kowloon, Hong Kong, China

Dr. Jun Wang of City University of Hong Kong

Topic:

The State of the Art of Neurodynamic Optimization - Past, Present, and Prospect

Biography:

Email:

Address:Hong Kong, China





Agenda

1:30 PM - 2:00 PM: Introduction

2:00 PM - 3:00 PM: Presentation

3:00 PM - 3:30 PM: Questions and Networking