Conference Speakers

 

Keynote Speaker I
Prof. Juyang Weng, Brain-Mind Institute and GENISAMA, USA
(IEEE Life Fellow)

Prof. Juyang Weng received the BS degree from Fudan University, in 1982, M. Sc. and PhD degrees from the University of Illinois at Urbana-Champaign, in 1985 and 1989, respectively, all in computer science.  He is a former faculty member of Department of Computer Science and Engineering, faculty member of the Cognitive Science Program, and faculty member of the Neuroscience Program at Michigan State University, East Lansing.  He was a visiting professor at the Computer Science School of Fudan University, Nov. 2003 - March 2014, and did sabbatical research at MIT, at Media Lab Fall 1999 – Spring 2000; and at Department of Brain and Cognitive Science Fall 2006-Spring 2007 and taught BCS9.915/EECS6.887 Computational Cognitive and Neural Development during Spring 2007.   Since the work of Cresceptron (ICCV 1993) the first deep learning neural networks for 3D world without post-selection misconduct, he expanded his research interests in biologically inspired systems to developmental learning, including perception, cognition, behaviors, motivation, machine thinking, and conscious learning models.  He has published over 300 research articles on related subjects, including task muddiness, intelligence metrics, brain-mind architectures, emergent Turing machines, autonomous programing for general purposes (APFGP), Post-Selection flaws in “deep learning”, vision, audition, touch, attention, detection, recognition, autonomous navigation, and natural language understanding.  He published with T. S. Huang and N. Ahuja a research monograph titled Motion and Structure from Image Sequences.  He authored a book titled Natural and Artificial Intelligence: Computational Introduction to Computational Brain-Mind.  Dr. Weng is an Editor-in-Chief of the International Journal of Humanoid Robotics, the Editor-in-Chief of the Brain-Mind Magazine, and an associate editor of the IEEE Transactions on Autonomous Mental Development (now Cognitive and Developmental Systems).  With others’ support, he initiated the series of International Conference on Development and Learning (ICDL), the IEEE Transactions on Autonomous Mental Development, the Brain-Mind Institute, and the startup GENISAMA LLC.  He was an associate editor of the IEEE Transactions on Pattern Recognition and Machine Intelligence and the IEEE Transactions on Image Processing.

Title of Speech:  The First Conscious Learning Algorithm Avoids “Deep Learning” Misconduct
Abstract: From a fruit fly to a human, with many animal species in between, do they share a set of biological mechanisms to regulate the lifelong development of the brains?  We have seen very impressive advances in understanding the principles of neuroscience.  However, what is still missing is a holistic algorithm that is both broad and deep.  By broad, we mean it approximates such mechanisms across a range of species. By deep, we mean that it specifies sufficient details so that the algorithm can be biologically and computationally verified and possibly corrected across a deep hierarchy of scales, from neurotransmitters, to cells, to brain patterns, to behaviors, to intelligence, to consciousness across the time span of a life.   This talk outlines such a conscious learning algorithm, the first in the category as far as the presenter is aware of, called Developmental Network 3 (DN-3).   All its predecessors, Cresceptron, IHDR, DN-1 and DN-2 were not capable of conscious learning till DN-3.  A major extension from DN-2 to DN-3 is that the model starts from a single cell inside the skull so that brain patterning is fully automatic in a coarse to fine way.   This biological model has been supported by computational experiments with real sensory data for vision, audition, natural languages, and planning, to be presented during the talk.  This first ever algorithm for conscious learning is free from “deep learning” misconduct, including ChatGPT.

 

Keynote Speaker II

Prof. Benjamin W. Wah, The Chinese University of Hong Kong, Hong Kong, China
(IEEE Fellow / ACM Fellow / AAAS Fellow)

Benjamin W. Wah is currently a Research Professor at the Chinese University of Hong Kong (CUHK) and Franklin W. Woeltge Emeritus Professor of Electrical and Computer Engineering at the University of Illinois, Urbana-Champaign, USA. He previously served as Provost and Wei Lun Professor of Computer Science and Engineering of CUHK, Chair, Research Grants Council of Hong Kong, as well as the Franklin W. Woeltge Professor of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, USA (2002-2011). He received his Ph.D. degree in computer science from the University of California, Berkeley, CA, in 1979. He has received several awards for his research and service contributions, which include the IEEE CS Technical Achievement Award (1998), the IEEE Millennium Medal (2000), the IEEE-CS W. Wallace-McDowell Award (2006), the Pan Wen-Yuan Outstanding Research Award (2006), the IEEE-CS Richard E. Merwin Award (2007), the IEEE-CS Technical Committee on Distributed Processing Outstanding Achievement Award (2007), the IEEE-CS Tsutomu Kanai Award (2009), and the Distinguished Alumni Award in Computer Science of the University of California, Berkeley (2011). Wah's current research interests are in the areas of big data and multimedia systems. Wah co-founded the IEEE Transactions on Knowledge and Data Engineering in 1988 and served as its Editor-in-Chief between 1993 and 1996, and is the Honorary Editor-in-Chief of Knowledge and Information Systems. He currently serves on the editorial boards of Information Sciences, International Journal on Artificial Intelligence Tools, Journal of VLSI Signal Processing, World Wide Web, and Journal of Computer Science and Technology. He has served the IEEE Computer Society in various capacities, including Vice President for Publications (1998 and 1999) and President (2001). He is a Fellow of the AAAS, ACM, and IEEE.

 

Keynote Speaker III

Prof. James Tin-Yau Kwok, Hong Kong University of Science and Technology, Hong Kong
(IEEE Fellow)

James Kwok is a Professor in the Department of Computer Science and Engineering, Hong Kong University of Science and Technology. He is an IEEE Fellow. Prof Kwok received his B.Sc. degree in Electrical and Electronic Engineering from the University of Hong Kong and his Ph.D. degree in computer science from the Hong Kong University of Science and Technology. He then joined the Department of Computer Science, Hong Kong Baptist University as an Assistant Professor. He returned to the Hong Kong University of Science and Technology and is now a Professor in the Department of Computer Science and Engineering. He is serving as an Associate Editor for the IEEE Transactions on Neural Networks and Learning Systems, Neural Networks, Neurocomputing, Artificial Intelligence Journal, International Journal of Data Science and Analytics, and on the Editorial Board of Machine Learning. He is also serving / served as Senior Area Chairs of major machine learning / AI conferences including NeurIPS, ICML, ICLR, IJCAI, and as Area Chairs of conferences including AAAI and ECML. He is recognized as the Most Influential Scholar Award Honorable Mention for "outstanding and vibrant contributions to the field of AAAI/IJCAI between 2009 and 2019". Prof Kwok will be the IJCAI-2025 Program Chair.

 

Keynote Speaker IV

Prof. Jie Yang, Shanghai Jiao Tong University, China

Jie Yang received a bachelor’s degree in Automatic Control in Shanghai Jiao Tong University, where a master’s degree in Pattern Recognition & Intelligent System was achieved three years later. In 1994, he received Ph.D. at Department of Computer Science, University of Hamburg, Germany. Now he is the Professor and Director of Institute of Image Processing and Pattern recognition in Shanghai Jiao Tong University. He is the principal investigator of more than 30 national and ministry scientific research projects in image processing, pattern recognition, data mining, and artificial intelligence. He has published six books，more than five hundreds of articles in national or international academic journals and conferences. Up to now, he has supervised 5 postdoctoral, 36 doctors and 66 masters, awarded eight research achievement prizes from ministry of Education, China and Shanghai municipality. Two Ph.D. dissertation he supervised was evaluated as “National Best Ph.D. Dissertation” in 2009, in 2017, in 2019.  He has owned 48 patents.

 

Keynote Speaker V

Prof. Qiu Daowen, Sun Yat-sen University, China

My main research outcomes have been in the following areas. (1) Quantum models of computation. (2) Quantum query algorithms. (3) Quantum cryptograpy and quantum communication. (4) Quantum states distinguishablility and quantum states cloning. (5) Theory of computation based on quantum and lattice-valued logic. (5) The applications of fuzzy and probabilistic automata to discrete event systems, focusing on diagnosability and supervisory control.