Keynote Speakers & Invited Speaker

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Keynote Speaker I

Prof. Qing Li (IEEE Fellow)
The Hong Kong Polytechnic University, Hong Kong, China

Qing Li received the B.Eng. degree in computer science from the Hunan University (Changsha), China, and the M.Sc. and Ph.D. degrees in computer science from the University of Southern California (Los Angeles), USA. He is a Chair Professor and the Head of Department of Computing, the Hong Kong Polytechnic University. His current research interests include multimodal data mining and management, conceptual data modeling, social media computing, Web services, and e-learning systems. He has authored/co-authored over 480 publications in the above areas. Prof. Li is also actively involved in the research community and has served as an associate editor of several technical journals, including IEEE Transactions on Artificial Intelligence, IEEE Transactions on Cognitive and Developmental Systems (TCDS), IEEE Transactions on Knowledge and Data Engineering (TKDE), the ACM Transactions on Internet Technology (TOIT), Data Science and Engineering, ​and World Wide Web, in addition to being a Conference and Program Chair/Co-Chair of numerous major international conferences. He is a fellow of IEEE, AAIA, and IEE/IET, in addition to being a distinguished member of CCF (China). He has sat/been sitting in the Steering Committees of ACM RecSys, IEEE U-MEDIA, DASFAA, WISE, FFD, and ICWL.

 

Keynote Speaker II

Prof. Nikola Kasabov (IEEE Fellow)
Auckland University of Technology, New Zealand

Professor Nikola Kasabov is Life Fellow of IEEE, Fellow of the Royal Society of New Zealand, Fellow of the INNS College of Fellows, DVF of the Royal Academy of Engineering UK. He is the Founding Director of the Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland and Professor at the School of Engineering, Computing and Mathematical Sciences at Auckland University of Technology, New Zealand. He is also George Moore Chair Professor of Data Analytics at the University of Ulster UK, Honorary Professor at the Teesside University UK and the University of Auckland NZ, Visiting Professor at the Bulgarian Academy of Sciences. Kasabov is Past President of the Asia Pacific Neural Network Society (APNNS) and the International Neural Network Society (INNS). He has been a chair and a member of several technical committees of IEEE Computational Intelligence Society and Distinguished Lecturer of IEEE (2012-2014). He is Editor of Springer Handbook of Bio-Neuroinformatics, EIC of Springer Series of Bio-and Neuro-systems and co-EIC of the Springer journal Evolving Systems. He is Associate Editor of several journals, including Neural Networks, IEEE TrNN, Tr CDS, Information Sciences, Applied Soft Computing. Kasabov holds MSc and PhD from TU Sofia, Bulgaria. His main research interests are in the areas of neural networks, intelligent information systems, soft computing, bioinformatics, neuroinformatics. He has published more than 680 publications, highly cited internationally. He has extensive academic experience at various academic and research organisations in Europe and Asia, including: TU Sofia Bulgaria; University of Essex UK; University of Otago, NZ; Advisory Professor at Shanghai Jiao Tong University and CASIA China; Visiting Professor at ETH/University of Zurich and Robert Gordon University UK; Visiting Scholar at University of Dalian, China. Kasabov has received a number of awards, among them: Doctor Honoris Causafrom Obuda University, Budapest; INNS Ada Lovelace Meritorious Service Award; NN Best Paper Award for 2016; APNNA ‘Outstanding Achievements Award’; INNS Gabor Award for ‘Outstanding contributions to engineering applications of neural networks’; EU Marie Curie Fellowship; Bayer Science Innovation Award; APNNA Excellent Service Award; RSNZ Science and Technology Medal; 2015 AUT Medal; Honorary Member of the Bulgarian, the Greek and the Scottish Societies for Computer Science (https://academics.aut.ac.nz/nkasabov).

Invited Speaker I

Assoc. Prof. Jiyi Li
Hokkaido University, Japan

Jiyi Li received the Ph.D. degree from the Graduate School of Informatics, Kyoto University, Japan. He is currently an Associate Professor with the Graduate School of Information Science and Technology, Hokkaido University, Japan. His research interests include crowdsourcing and human computation, data mining, natural language processing, data engineering, and multimedia. He has published more than 90 papers in major international conferences and journals including AAAI, IJCAI, WWW, SIGIR, ACL, EMNLP, MM, CIKM and ICASSP. He received the 19th DBSJ Kambayashi Young Researcher Award from the Database Society of Japan.

 

Invited Speaker II

Assistant Professor Dr. Guoming Wang
Zhejiang University, China

Dr. Wang is an Assistant Professor at Zhejiang University, specializing in multimodal intelligence, privacy-preserving machine learning, and AI-driven healthcare applications. He earned his Ph.D. in 2020 from Nanyang Technological University (Singapore), where his doctoral research focused on advanced privacy technologies, including cryptographic protocols, differential privacy, homomorphic encryption, and their implementation in secure electronic medical systems.

Since joining Zhejiang University in 2020, Dr. Wang has pioneered research in multimodal machine learning and retrieval-augmented large language models, with an emphasis on enhancing AI reasoning capabilities. His academic excellence is reflected in over 20 publications at top-tier venues such as CVPR, AAAI, ACM Multimedia (ACM MM), COLING, and IEEE Global Communications Conference (GLOBECOM), and his recent recognition as an Industry Expert at ACM MM 2024.

Translating Research into Impact:
Dr. Wang leads AI-driven medical initiatives that bridge cutting-edge technology with clinical practice:
*Developed an AI-powered healthcare system adopted by 20+ hospitals.
*Designed intelligent platforms enabling 20+ physicians to advance research in disease prediction for complex conditions including migraine, pancreatic cancer, cardiovascular disorders, pulmonary infections, and diabetic nephropathy through multimodal learning.
His work exemplifies a commitment to advancing both theoretical frontiers of machine learning and their transformative applications in global healthcare.