Keynote Speakers

Yiu-ming Cheung is currently a Chair Professor (Artificial Intelligence) of the Department of Computer Science, Dean of Institute for Research and Continuing Education (IRACE), and Associate Director of Institute of Computational and Theoretical Studies in Hong Kong Baptist University (HKBU). He received PhD degree from Department of Computer Science and Engineering at The Chinese University of Hong Kong in 2000, and then joined the Department of Computer Science at HKBU in 2001. He is an IEEE Fellow, AAAS Fellow, IET Fellow, AAIA Fellow, and British Computer Society (BCS) Fellow. He is the Awardee of RGC Senior Research Fellow with receiving a fellowship grant of HK$7.8 million over a period of 60 months. Since 2019, he has been ranked the World’s Top 1% Most-cited Scientists in the field of Artificial Intelligence and Image Processing by Stanford University for six consecutive years. He was elected as a Distinguished Lecturer of IEEE Computational Intelligence Society in 2020, and named a Chair Professor of Changjiang Scholars Program by the Ministry of Education of the People’s Republic of China for the dedication and exceptional achievements in his academic career. Also, he is the Editor-in-Chief of IEEE Transactions on Emerging Topics in Computational Intelligence.
His research interests include machine learning and visual computing, as well as their applications in data science, pattern recognition, multi-objective optimization, and information security. He has published over 300 articles in the high-quality conferences and journals, including TPAMI, TNNLS, TIFS, TIP, TMM, TKDE, TCYB, CVPR, IJCAI, AAAI, and so on. His four co-authored papers have been selected as ESI Highly Cited Papers (i.e. listed in Top 1% globally in the corresponding discipline). Moreover, he has been granted one Chinese patent and two US patents. Subsequently, the underlying technique of his eye-gaze tracking patent has been successfully applied to develop the first mobile app for fatigue driving detection. It turns out that, selected from 1000 new inventions and products of 700+ competition teams from 40 countries, he was awarded two most prestigious prizes: (1) the Gold Medal with Distinction (i.e. the highest grade in Gold Medals) and (2) Swiss Automobile Club Prize, in the 45th International Exhibition of Invention, Geneva, Switzerland, on March 29-April 2, 2017, in recognition of his innovative work. Also, he was the Gold Award Winner of Hong Kong Innovative Invention Award in the Seventh Hong Kong Innovative Technologies Achievement Award 2017. In addition, he won the Gold Medal with Congratulations of Jury (i.e. the highest grade in Gold Medals) and the Award of Excellence from Romania, respectively, at the 46th International Exhibition of Inventions of Geneva 2018 with his invention “Lip-password: Double Security System for Identity Authentication”. He was the recipient of: (1) 2023-2024 President’s Award for Outstanding Performance in Scholarly Work at HKBU, (2) HKBU Innovation Award 2024, (3) 2023 APNNS Outstanding Achievement Award, (4) Best Research Award of Department of Computer Science at HKBU in 2011 and 2021, respectively, (5) 2022-23 Faculty Research Excellence Paper Award in HKBU, (6) Best in Theoretical Paper Award in WI-IAT’2020, (7)  Best Student Paper Award in ISMIS’2018, and (8) Best Paper Awards in DOCS’2024, SEAL’2017, ISICA’2017, ICNC- FSKD’2014, and IEEE IWDVT’2005.
He is the Founding Chairman of IEEE (Hong Kong) Computational Intelligence Chapter and the Chair of Technical Community on Intelligent Informatics (TCII) of IEEE Computer Society. He has served in various capacities (e.g., Organizing Committee Chair, Program Committee Chair, Program Committee Area Chair, and Financial Chair) at several top-tier international conferences, including IJCAI’2021, ICPR’2020, ICDM’2017 & 2018, WCCI’2016, WI-IAT’2012, ICDM’2006 & WI-IAT’2006, to name a few. He is an Associate Editor of several prestigious journals, including IEEE Transactions on Cybernetics, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Neural Networks and Learning Systems (2014-2020), Pattern Recognition, Pattern Recognition Letters, Knowledge and Information Systems (KAIS), and Neurocomputing, as well as the Guest Editor in several international journals. Currently, he is an Engineering Panel member of Research Grants Council, Hong Kong, a member of assessment panel of Enterprise Support Scheme (ESS) under the Innovation and Technology Fund (ITF), and a Fellow Evaluation Committee member of IEEE Computational Intelligence Society and IEEE Computer Society, respectively.

Speech Title: Deep Long-tailed Data Learning towards Visual Recognition

Abstract: Although deep learning has made great progress, a good model often requires a large amount of artificially balanced and annotated data. Unfortunately, real-world data are often unbalanced, typically exhibiting a long-tailed distribution, which refers to a small number of classes with abundant training samples but the remaining large number of classes only with very few training instances. Under the circumstances, the performance of deep learning models trained on long-tailed data declines sharply in the tail classes. However, tail classes cannot be ignored in various situations such as rare disease diagnosis, and anomaly detection. Subsequently, long-tailed data is still very challenging to deep learning. In this talk, the impact of long-tailed data on deep learning models will be first introduced. Then, the research progress in this area will be reviewed, including some representative methods in the literature. Lastly, the potential research directions in this field will be discussed.

Ling Wang received both B.Sc. and Ph.D. degrees from Tsinghua University in 1995 and 1999, and now is a tenured Full Professor with Tsinghua Univ. His research interests mainly include artificial intelligence, intelligent optimization, scheduling and applications. He has authored 5 academic books and 450+ SCI-indexed papers. His publications have attracted over 40K Google Scholar Citations. He is the Editor-in-Chief of  Expert Systems with Applications, Swarm and Evolutionary Computation, International J of Automation and Control, Complex System Modeling and Simulation, and the Associate Editor of IEEE Trans on Evolutionary Computation, and the Editorial Board Member of several journals like Memetic Computing, Control Theory & Applications, etc. Prof. Wang received National Natural Science Award of China (2nd Prize), Natural Science Award of the Ministry of Education of China (1st Prize and 2nd Prize), Technology Innovation Award (1st Prize) and Natural Science Award (1st Prize) of China Simulation Federation. He also received INFORMS Franz Edelman Finalist Award, and the Best Paper Awards of several journals and conferences like Acta Automatica Sinica, Control Theory & Applications. He was the recipient of National Natural Science Fund for Distinguished Young Scholars of China (2015), Young Talent of Science and Technology of Beijing City, New Century Excellent Talent in University by the MOE of China, Academic Young Talent of Tsinghua University, Young Scientist Award of CAA, Chinese Most Cited Researcher and Clarivate-Highly Cited Researcher, IEEE TEVC Outstanding Associate Editor.

Speech Title: Research Development of Optimization Scheduling for Smart Manufacturing and Service

Abstract: In this talk I will first introduce the background and significance of the research about optimization scheduling for manufacturing and service systems, and then explain the classification and challenges on the research about optimization. Finally I will point out the important issues and development directions about optimization and scheduling based on several application fields and scenarios.

Liang Xiao is IEEE Fellow and a Professor in the Department of Informatics and Communication Engineering, Xiamen University. She has served in several editorial roles, including an associate editor of IEEE Transactions on Information Forensics & Security, IEEE Transactions on Communication, IEEE Transactions on Wireless Communication and IEEE Transactions on Dependable and Secure Computing, and Guest Editor of IEEE Journal on Selected Topics in Signal Processing. Her research interests include wireless security, privacy protection, and wireless communications. She published three books and three book chapters. She won 2024 IEEE ComSoc Asia-Pacific Outstanding Paper Award, as well as the best paper award for 2017 IEEE ICC, 2018 IEEE ICCS and 2016 IEEE INFOCOM Bigsecurity WS. She was 2022-2023 IEEE ComSoc Distinguished Lecturer.

Speech Title: Environment-Aware Collaborative Vehicular Perception Against Jamming and Interference

Abstract: Collaborative vehicular perception suffers from prolonged perception latency and significant perception errors against jamming and interference. In this report, we discuss reinforcement learning-based collaborative vehicular perception scheme to enhance perception accuracy and speed with incorporating the environmental features such as traffic density and building layouts in the state formulation. The critic region of feature maps, transmit power and channels are chosen to enhance the utility as the weighted sum of perception accuracy, speed, and the minimum latency requirement for data sharing. The upper performance bound of perception accuracy and speed is provided based on the Stackelberg equilibrium of the game between CAVs and the jammer, revealing the impact of maximum jamming power, channel gains, data size and point cloud resolution on the perception performance.