Prof. Shui Yu
IEEE Fellow
University of Technology Sydney, Australia

Shui Yu is a Professor of School of Computer Science, University of Technology Sydney, Australia. His research interest includes Cybersecurity, Network Science, Big Data, and Mathematical Modelling. He has published seven monographs and edited two books, more than 600 technical papers at different venues, such as IEEE TDSC, TPDS, TC, TIFS, TMC, TKDE, TETC, ToN, and INFOCOM. His current h-index is 79. Professor Yu promoted the research field of networking for big data since 2013, and his research outputs have been widely adopted by industrial systems, such as Amazon cloud security. He is currently serving the editorial boards of IEEE Communications Surveys and Tutorials (Area Editor) and IEEE Internet of Things Journal (Editor). He is a Distinguished Visitor of IEEE Computer Society, and an elected member of Board of Governors of IEEE VTS and IEEE ComSoc, respectively. He is a member of ACM and AAAS, and a Fellow of IEEE.

Speech title "Mathematical Artificial Intelligence and Applications"

Abstract: Artificial Intelligence is a leading topic in both academia and industry. However, we do not have decent theoretical understanding of the various models, such as the deep learning models. As a matter of fact, we are at the doorstep of the theoretical breakthrough for AI. In this talk, we firstly present the basic concepts of differential geometry, a powerful tool for the study of high dimension space. Secondly, we discuss some applications of the set of tools for unprecedented AI problems. We hope and believe the talk will shed light on the promising field for interested audience.

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

Qing Li is a Chair Professor and Head of the Department of Computing, the Hong Kong Polytechnic University. He received his B.Eng. from Hunan University (Changsha), and M.Sc. and Ph.D. degrees from the University of Southern California (Los Angeles), all in computer science. His research interests include multi-modal data management, conceptual data modeling, social media, Web services, and e-learning systems. He has authored/co-authored over 500 publications in these areas, with over 41,000 citations and H-index of 83 (source: Google Scholars). He is actively involved in the research community and has served as Editor-in-Chief of Computer & Education: X Realitty (CEXR) by Elsevier, associate editor of IEEE Transactions on Artificial Intelligence (TAI), IEEE Transactions on Cognitive and Developmental Systems (TCDS), IEEE Transactions on Knowledge and Data Engineering (TKDE), ACM Transactions on Internet Technology (TOIT), Data Science and Engineering (DSE), and World Wide Web (WWW) Journal, in addition to being a Conference and Program Chair/Co-Chair of numerous major international conferences. He also sits/sat in the Steering Committees of DASFAA, ER, ACM RecSys, IEEE U-MEDIA, and ICWL. Prof. Li is a Fellow of IEEE, AAIA, and IET.

Speech Title "KCUBE - A Knowledge Graph University Curriculum Framework for Student Advising and Career Planning"

Abstract: Knowledge representations and interactions are at the forefront of teaching, learning, and career planning activities in all endeavors of education and career development. University students are increasingly faced with a myriad of interdisciplinary topics that are seemingly unrelated when unstructured knowledge representations are presented, especially during advising and career orientation sessions. This is especially challenging in fast-changing technical domains such as Computer and Data Science where university curricula are reviewed on an annual basis. This makes it increasingly difficult for instructors and administrators to present both the big picture as well as the detailed knowledge components of degree programs to students when choosing a career or establishing a plan of study and assessment. This paper introduces the KCUBE project, a virtual reality knowledge graph framework for structuring and presenting both the overall view of the Computer Science curriculum taught in the Department of Computing at the Hong Kong Polytechnic University as well as the scheduling alternatives in managing course content and presentation views by instructors and students. We employ computational information storage and retrieval methods, machine learning, and interactive virtual reality to better understand, manipulate, and visualize abstract concepts and relationships in the development of teaching and learning activities in our department.

Prof. Sam Kwong
IEEE Fellow
Lingnan University, Hong Kong

Professor KWONG Sam Tak Wu is the Associate Vice-President (Strategic Research), J.K. Lee Chair Professor of Computational Intelligence, the Dean of the School of Graduate Studies and the Acting Dean of the School of Data Science of Lingnan University. Professor Kwong is a distinguished scholar in evolutionary computation, artificial intelligence (AI) solutions, and image/video processing, with a strong record of scientific innovations and real-world impacts. Professor Kwong was listed as the World’s Top 2% Scientists by Stanford University since 2022 and one of the most highly cited researchers by Clarivate in 2022 and 2023. He has also been actively engaged in knowledge transfer between academia and industry. He was elevated to IEEE Fellow in 2014 for his contributions to optimization techniques in cybernetics and video coding. He was a Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA) in 2022, and the President of the IEEE Systems, Man, and Cybernetics Society (SMCS) in 2021-23. He is a fellow of US National Academy of Inventors (NAI) and the Hong Kong Academy Awards of Engineering and Sciences (HKAES). Professor Kwong has a prolific publication record with over 350 journal articles, and 160 conference papers with an h-index of 84 based on Google Scholar. He is currently the associate editor of a number of leading IEEE transaction journals.

Prof. Wenhong Tian
University of Electronic and Science Technology of China, China

Tian Wenhong, a professor and doctoral supervisor, holds a Ph.D. in Computer Science from North Carolina State University in the United States. The current director of the Advanced Computing Laboratory at the University of Electronic Science and Technology of China, director of the Sichuan Intelligent Home Information Technology Engineering Research Center, member of the Academic Committee of the School of Software, and leader of the Cloud Computing discipline.
His research focuses on optimizing and scheduling computing resources in cloud computing, big data, and AI platforms, as well as deep learning based image recognition and its applications. He is a Senior Member of the Chinese Computer Society (CCF) and IEEE Senior Member. He has been selected as one of the first batch of "Western Light" talent programs of the Chinese Academy of Sciences, Academic and technical leaders and reserve candidates in Sichuan Province, Chengdu Special Experts (Rong Piao Plan), and the "Spark Plan" of the University of Electronic Science and Technology of China.
He has successively led one general project of the National Natural Science Foundation of China and four international regional cooperation projects, as well as one of the first batch of national key research and development projects for artificial intelligence by the Ministry of Science and Technology of 2030, and more than 20 other projects; In recent years, more than 50 invention patents have been applied for, and more than 20 invention patents have been granted in China and 1 patent has been granted in the United States; Published over 100 high-level papers as the first or corresponding author, and edited 7 Chinese and English monographs. After nearly 20 years of deep cultivation in the field of industry university research cooperation, it has produced good social and economic benefits. In 2023, it was awarded the "Spark Award" by Huawei and was one of the nine winners of the University of Electronic Science and Technology of China.