Keynote Speakers

Title: to be confirmed.

Professor Danilo Mandic

Fellow of the Institute of Electrical and Electronics Engineering (IEEE), President of the International Neural Network Society (INNS)
Imperial College, UK

Title: to be confirmed

Professor Ong Yew Soon

Fellow of the Institute of Electrical and Electronics Engineering (IEEE)
Nanyang Technological University, Singapore

Title: Brain Cognition Inspired Artificial Intelligence

Professor Guoyin Wang

Vice-President of the Chinese Association for Artificial Intelligence (CAAI), President of Chongqing Normal University
Chongqing Normal University, China

Abstract: With the synergy of big data, big computing power and large model, artificial intelligence (AI) has made breakthrough progress in surpassing some key human intelligence abilities such as visual intelligence, auditory intelligence, decision intelligence, and language intelligence in recent years. However, AI systems surpass certain human intelligence abilities in a statistical sense as a whole only. They are not true realization of these human intelligence abilities and behaviors. This talk reviews the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on Marr's three-layer framework, explores and analyses the limitations of the current development of AI. At the hardware implementation layer, the differences and inconsistencies between the mechanisms of human brain neurons and their neural system connections and those of neurons and their connections in artificial neural networks (ANNs) cause two problems. Firstly, it causes the working mechanism of deep neural networks being different from the mechanism of human cognition, which is manifested in contradictory phenomena such as the recognition results of deep neural networks being very different from human cognitive understanding. Secondly, it causes poor performance of the spiking neural networks (SNNs). At the representation and algorithm layer, there are also many differences and inconsistencies between the problem-solving strategies and mechanisms of AI systems and those of human brains, which cause inconsistencies and conflicts between the two in terms of intelligent cognition. At the computational theory layer, there are still inconsistencies between the computational and processing mechanisms of AI systems and that of human brains. In view of the above limitations, eight important future research directions and their scientific issues that need to be focused on in brain-inspired AI research are proposed: 1) Highly imitated bionic information processing; 2) Large-scale deep learning model balancing structure and function; 3) Multi-granularity joint problem solving bidirectionally driven by data and knowledge; 4) AI models simulating specific brain structures; 5) Collaborative processing mechanism with physical separation of perceptual processing and interpretive analysis; 6) Embodied intelligence integrating brain cognitive mechanism and AI computation mechanisms; 7) Intelligence simulation from individual intelligence to group intelligence (social intelligence); 8) Artificial intelligence assisted brain cognitive intelligence (AI4BI).

Short Bio: Guoyin Wang received the B.S., M.S., and Ph.D. degrees from Xi'an Jiaotong University, Xian, China, in 1992, 1994, and 1996, respectively. He worked at the University of North Texas, and the University of Regina, Canada, as a visiting scholar during 1998-1999. He had worked at the Chongqing University of Posts and Telecommunications during 1996-2024, where he was a professor, the Vice-President of the University, the director of the Chongqing Key Laboratory of Computational Intelligence, the director of the Key Laboratory of Cyberspace Big Data Intelligent Security of the Ministry of Education, the director of Tourism Multi-source Data Perception and Decision Technology of the Ministry of Culture and Tourism, and the director of the Sichuan-Chongqing Joint Key Laboratory of Digital Economy Intelligence and Security. He was the director of the Institute of Electronic Information Technology, Chongqing Institute of Green and Intelligent Technology, CAS, China, 2011-2017. He has been serving as the President of Chongqing Normal University since June 2024. He is the author of over 10 books, the editor of dozens of proceedings of international and national conferences and has more than 300 reviewed research publications. His research interests include rough sets, granular computing, machine learning, knowledge technology, data mining, neural network, cognitive computing, etc. Dr. Wang was the President of International Rough Set Society (IRSS) 2014-2017, and a council member of the China Computer Federation (CCF) 2008-2023. He is currently a Vice-President of the Chinese Association for Artificial Intelligence (CAAI), and the President of Chongqing Association for Artificial Intelligence (CQAAI). He is a Fellow of IRSS, I2CICC, CAAI and CCF.

More To Be Confirmed.

Highlighted Keynote Speakers in the Past WI-IAT Editions

Edward Feigenbaum (Turing Award Laureate)   WI-IAT 2001, WI-IAT 2012
Lotfi A. Zadeh   WI-IAT 2003
John McCarthy (Turing Award Laureate)   WI-IAT 2004
Tom M. Mitchell   WI-IAT 2004, WI-IAT 2021
Richard M. Karp (Turing Award Laureate)   WI-IAT 2007
Yuichiro Anzai   WI-IAT 2011
John Hopcroft (Turing Award Laureate)   WI-IAT 2013
Andrew Chi-Chih Yao (Turing Award Laureate)   WI-IAT 2014
Joseph Sifakis (Turing Award Laureate)   WI-IAT 2015, WI-IAT 2021
Butler Lampson (Turing Award Laureate)   WI 2016
Leslie Valiant (Turing Award Laureate)   WI 2016, WI-IAT 2021
Raj Reddy (Turing Award Laureate)   WI 2017
Frank van Harmelon   WI-IAT 2021