Prof. Yi Pan

 Shenzhen University of Advanced Technolog, China

Dr. Yi Pan is currently a Chair Professor and Dean of Faculty of Computer Science and Artificial Intelligence at Shenzhen University of Advanced Technology, China and a Regents’ Professor Emeritus at Georgia State University, USA. He served as Chair of Computer Science Department at Georgia State University from 2005 to 2020. He has also served as an Interim Associate Dean and Chair of Biology Department during 2013-2017. Dr. Pan joined Georgia State University in 2000, was promoted to full professor in 2004, named a Distinguished University Professor in 2013 and designated a Regents’ Professor (the highest recognition given to a faculty member by the University System of Georgia) in 2015. Dr. Yi Pan is Fellow of American Institute for Medical and Biological Engineering, Foreign Member of Russian Academy of Engineering, Foreign member of Ukrainian Academy of Engineering Science, Member of European Academy of Sciences and Arts, Distinguished Fellow of International Engineering and Technology Institute,  Fellow of the Royal Society for Public Health, Fellow of the Institute of Engineering and Technology, and Fellow of the Japan Society for the Promotion of Science. His work has been cited more than 34000 times based on Google Scholar and his current h-index is 104. He was selected as a top 0.05% scholar in the world and ranked the world's No. 4 top scholar in computational biology over the past five years by ScholarGPS in 2024 and 2025.

Prof. Zhiguo Gong

University of Macau, China

Prof. Zhiguo Gong, a Senior Member of IEEE, received his Ph.D. degree in Computer Science and Engineering from The Chinese University of Hong Kong in 1999. He is currently a Full Professor in the Department of Computer and Information Science at the Faculty of Science and Technology, University of Macau. Before joining the University of Macau, he had been a faculty member at Nanyang Technological University in Singapore for several years. His research interests include big data management and mining, social network analysis, web information retrieval, and machine learning. Prof. Gong has published extensively in leading international journals and conferences. He currently serves as an Associate Editor for the Journal of Web Engineering and has served as a guest editor for several international journals. He has also been actively involved in organizing international conferences and workshops, serving as general chair, program committee chair, and program committee member for numerous conferences in the fields of data engineering and information systems.

Speech Title: Graph Learning for Recommender Systems

Abstract: Despite years of development, recommender algorithms continue to attract significant attention from both academic and industry communities, driven by ongoing practical demands. In recent years, Graph Neural Network (GNN) techniques have been increasingly integrated into recommender system models, offering new capabilities and insights. In this talk, I will provide a concise overview of the evolution of graph-based learning approaches in recommender systems, along with some findings from our recent research in this area.

Prof. Zhen Liang

Shenzhen University, China

Zhen Liang is a National High-Level Young Talent of China, Vice Dean of the Graduate School, Professor, and Ph.D. Supervisor at Shenzhen University. She previously worked at NeuroSky in the United States and Kyoto University in Japan. Her research focuses on brain–computer interfaces, neuroimaging, and artificial intelligence. She has published over 70 high-impact papers as first or corresponding author, including in Cell Reports Medicine and Advanced Science. She serves on the editorial boards of IEEE TAFFC, IEEE TNSRE, Neural Networks, and Cyborg and Bionic Systems. She has led multiple projects funded by the National Natural Science Foundation of China (NSFC) and received numerous honors, including the Shi Qingyun Women Scientist Award, Guangdong Distinguished Young Talent, Shenzhen Overseas High-Level Talent, the IEEE SMC Winner Award, and the Shenzhen AI Outstanding Service Award. She is also the Co-founder and Chief Scientist of Shenzhen Pengrui Brain Science Technology Co., Ltd., dedicated to advancing the clinical translation of brain–computer interface technologies.

Speech Title: Brain Reading–Writing Synergy for Brain Intelligence

Abstract:Brain–computer interfaces (BCIs) are evolving from unidirectional brain reading toward closed-loop brain intelligence enabled by the synergy of brain reading and brain writing. Brain reading leverages intelligent computing to decode neural activity and interpret human perception, cognition, and behavioral intentions, whereas brain writing employs precision neuromodulation to actively regulate and optimize brain function. Their deep integration provides a new paradigm for developing intelligent BCI systems with capabilities for perception, decision-making, regulation, and continual learning. This talk will review recent advances in brain reading–writing synergy, covering intelligent neural decoding, multimodal brain data analytics, precision neuromodulation, and closed-loop brain–computer interfaces. It will further discuss the future directions of brain intelligence driven by the convergence of artificial intelligence and brain science, as well as its promising applications in neurological disease diagnosis and treatment, cognitive enhancement, and human–AI collaborative intelligence.

Prof. Laizhong Cui

Shenzhen University, China

Laizhong Cui is the Distinguished Professor and Doctoral Supervisor of the College of Computer Science and Software Engineering, Shenzhen University; Vice Dean of the College; Assistant Director of Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ); Executive Director of Guangdong-Hong Kong Joint Collaborative Innovation Center for Modern Information Services. His research focuses on computer networks, distributed machine learning and data science. He has led several key projects, including the Joint Fund of National Natural Science Foundation of China, National Key R&D Program, Outstanding Youth Team Program of Guangdong Natural Science Foundation, Shenzhen Outstanding Youth Fund and other research projects. He has published over 200 papers in top-tier journals and conferences including TON, JSAC, TMC, TPDS, TC, TDSC, TKDE, NDSS, INFOCOM, MM, AAAI and ICLR. He is the National-level Young Talent. His honors include the First Prize of Natural Science Award of Chinese Association for Artificial Intelligence, First Prize of Technological Invention Award of China Institute of Communications, Fok Ying Tung Young Scientist Award and Shenzhen Youth Science and Technology Award.

Speech Title: Sensing-Transmission-Computation Integrated Adaptive Intelligent Streaming Media Technology

Abstract: With the growing popularity of streaming media services and applications such as virtual/augmented reality and video analytics, interactive streaming data has become the dominant traffic on the Internet. Considering users’ personalized interaction requirements and the characteristics of streaming media services, optimizing the adaptive mechanisms for streaming media transmission is of great significance. This presentation will introduce our recent research progress on Sensing-Transmission-Computation integrated adaptive intelligent streaming media transmission, covering: adaptive tile segmentation schemes, transmission-computation coordination mechanisms for panoramic video, and collaborative scheduling for batch transmission and batch processing of video data.