Speakers

Prof. Yan Zhang

IEEE Fellow

Member, Academia Europaea

Member, Royal Norwegian Society of Sciences and Letters Academy

Member, Norwegian Academy of Technological Sciences

"Highly Cited Researcher"

University of Oslo, Norway

Profile:  

Yan Zhang is currently a Full Professor with the Department of Informatics, University of Oslo, Norway. His research interests include next-generation wireless networks leading to 6G, green and secure cyber-physical systems. Dr. Zhang is an Editor for several IEEE transactions/magazine. Since 2018, Prof. Zhang has been listed as a Highly Cited Researcher by Clarivate Analytics (i.e., Web of Science). He is Fellow of IEEE, Fellow of IET, elected member of Academia Europaea (MAE), elected member of the Royal Norwegian Society of Sciences and Letters (DKNVS), and elected member of Norwegian Academy of Technological Sciences (NTVA).

Speech Title: Efficiency and Privacy in Distributed Federated Learning

Abstract: In this talk, we mainly introduce our recent major contributions in the field of distributed federated learning. We propose new solutions to address the computation, communications, and energy efficiency problems in federated learning. We exploit Blockchain to address the parameter/model privacy preservation in federated learning, while “Blockchain + federated learning” is currently a very active research field. We also present energy-efficient scheme when federated learning as distributed computing tasks in computing power networks. Several open issues have been pointed out as well in the related field.

Prof.  Qun Jin

Foreign fellow of the Engineering Academy of Japan (EAJ)

IEEE Senior Member

Waseda University, Japan

Profile:  

Qun Jin is a professor in the Department of Human Informatics and Cognitive Sciences, Faculty of Human Sciences, Waseda University, Japan. He has been extensively engaged in research works in the fields of computer science, information systems, and human informatics, with a focus on understanding and supporting humans through convergent research. His recent research interests cover behavior and cognitive informatics, artificial intelligence and machine learning, big data, personal analytics and individual modeling, trustworthy platforms for data federation, sharing, and utilization, cyber-physical-social systems, and applications in healthcare and learning support and for the realization of a carbon-neutral society. He authored or co-authored several monographs and more than 400 refereed papers published in academic journals and international conference proceedings. He served as a general chair, program chair, and keynote speaker for numerous IEEE/ACM sponsored international conferences. He served as a guest editor in recent years for IEEE Transactions on Industrial Informatics, IEEE Transactions on Computational Social Systems, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Emerging Topics in Computing, IEEE MultiMedia, and IEEE Cloud Computing. He is a foreign fellow of the Engineering Academy of Japan (EAJ). 

More information can be found athttps://researchmap.jp/jinqun/?lang=en.

Speech Title: Understanding and Supporting Humans through Convergent Research and Technology Convergence

Abstract: The grand challenges of today, such as protecting human health, cannot be solved by one discipline alone. It becomes essential and effective to make comprehensive use of the convergence knowledge, the merging of technologies, approaches, and insights from widely diverse fields through convergent research, to accurately respond to various societal issues. In this talk, after introducing the promising paradigm of convergent research and the concept of convergence knowledge and technology convergence, we will depict our vision on technology for the common good and computing for human well-being. We will further present our recent work on understanding and supporting humans through convergent research and technology convergence of AI, big data and IoT, and discuss important issues on privacy-preserving data analytics and solutions to promote human well-being.

Prof. Zhaolong Ning

IEEE Senior Member

Chongqing University of Posts and Telecommunications, China

Profile:  

Dr. Ning received the MS and PhD degrees from Northeastern University, China. From 2013 to 2014, he was a research assist at the Kyushu University, Japan. From 2014 to 2020, he was an assistant and associate professor at the Dalian University of Technology, China. From 2019 to 2021, he was a Hong Kong Scholar at The University of Hong Kong. Currently, he is a full professor with the Chongqing University of Posts and Telecommunications, China. He has published more than 150 scientific papers in international journals and conferences, such as TMC, JSAC, Mobicom, and so on. Two journal papers win the best paper award of IEEE TVT and IEEE Systems Journals, and 6 conference papers win the best paper award. His research interests include Internet of things, vehicular edge computing, and artificial intelligence. He is a Highly Cited Researcher (Clarivate) and a Chinese Highly Cited Researcher (Elsevier) since 2020. He is the associate editor or lead guest editor of 8 journals. He is an IET Fellow, an EAI Fellow, and a Senior Member of IEEE.

Speech Title: User Association and Trajectory Optimization for IRS-Assisted UAV Communications

Abstract: Due to the flexibility, low cost, and easy deployment characteristics of UAVs, they are widely utilized in wireless communication networks and can provide temporary communication services in areas with weak or congested network coverage. However, due to the complexity of the communication environment, there might be obstructions between UAVs and users. Intelligent Reflecting Surfaces (IRS), as one of the significant new technologies in future 6G, play a role in constructing virtual Line-of-Sight (LoS) paths, bringing a new network paradigm to future communications aimed at creating an intelligently controllable wireless communication environment. To fully leverage IRS resources in IRS-assisted UAV communication networks, this talk explores the application of multiple IRS-assisted UAV communication networks in suburban and urban scenarios.

Assoc. Prof. Por Lip Yee

University of Malaya, Malaysia

Profile:  

Lip Yee received his Ph.D. from the University of Malaya, Malaysia under the supervision of Prof. Abdullah bin Gani in 2012. Currently, he is an Assoc. Professor at the Department of System and Computer Technology, Faculty of Computer Science and Information Technology, University of Malaya, Malaysia. He is also a senior member of IEEE. Lip Yee and his team were the first few pioneers who received IRPA, E-Science, FRGS, ERGS, PRGS, HIR and IIRG grants. He was the first person who managed to secure 2 E-Science funds with the role of PI in 2008. He was also the first person at the FCSIT who managed to secure the PRGS and ERGS grants. Besides collaborators from Malaysia, Lip Yee also has international collaborators from France, UK New Zealand, Turkey, Thailand and China. He also established his connections with his national and international collaborators with some industrial partners in Malaysia and other countries.