Keynote Speaker I
Prof. Abbas Jamalipour
The University of Sydney, Australia
(IEEE Fellow)
Abbas Jamalipour is the Chair Professor of Ubiquitous Mobile Networking at The University of Sydney and the Editor-in-Chief, IEEE Transactions on Vehicular Technology. He holds a PhD in Electrical Engineering from Nagoya University, Japan; and is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), the Institute of Electrical, Information, and Communication Engineers (IEICE), and the Institution of Engineers Australia (IEA), an ACM Professional Member, and an IEEE Distinguished Speaker. He has authored nine technical books, eleven book chapters, over 550 technical papers, and five patents, all in the field of wireless communications. Dr. Jamalipour was the President (2020-21), Executive Vice-President (2018-19), and has been an elected voting member of the Board of Governors of the IEEE Vehicular Technology Society since 2014. Previously, he served as the Editor-in-Chief IEEE Wireless Communications, Vice-President Conferences, and a member of Board of Governors of the IEEE Communications Society. He is on the editorial board of the IEEE Access Journal; member of the Advisory Board of IEEE Internet of Things Journal, and an editor for several other journals.
He has been a General Chair or Technical Program Chair for a number of conferences, including IEEE ICC, GLOBECOM, VTC, WCNC and PIMRC. He is the recipient of a number of prestigious awards such as the 2019 IEEE ComSoc Distinguished Technical Achievement Award in Green Communications, the 2016 IEEE ComSoc Distinguished Technical Achievement Award in Communications Switching and Routing, the 2010 IEEE ComSoc Harold Sobol Award, the 2006 IEEE ComSoc Best Tutorial Paper Award, as well as over fifteen Best Paper Awards. He has been a General Chair or Technical Program Chair for a number of conferences, including IEEE ICC, GLOBECOM, VTC, WCNC and PIMRC, and Chair IEEE High Performance Switching and Routing Steering Committee (2018-2021). He is the recipient of a number of prestigious awards such as the 2019 IEEE ComSoc Distinguished Technical Achievement Award in Green Communications, the 2016 IEEE ComSoc Distinguished Technical Achievement Award in Communications Switching and Routing, the 2010 IEEE ComSoc Harold Sobol Award, the 2006 IEEE ComSoc Best Tutorial Paper Award, as well as over fifteen Best Paper Awards.
Keynote Speaker II
Prof. Xudong Jiang
Nanyang Technological University, Singapore
(IEEE Fellow)
Biodata: Xudong Jiang, IEEE Fellow, received the B.Eng. and M.Eng. from University of Electronic Science and Technology of China (UESTC), and the Ph.D. degree from Helmut Schmidt University, Hamburg, Germany. During his work in UESTC, he received two Science and Technology Awards from the Ministry for Electronic Industry of China. From 1998 to 2004, he was with the Institute for Infocomm Research, A-Star, Singapore, as a Lead Scientist and the Head of the Biometrics Laboratory, where he developed a system that achieved the most efficiency and the second most accuracy at the International Fingerprint Verification Competition in 2000. He joined Nanyang Technological University (NTU), Singapore, as a Faculty Member, in 2004, and served as the Director of the Centre for Information Security from 2005 to 2011. Currently, he is a professor of NTU. Dr Jiang holds 7 patents and has authored over 200 papers with over 40 papers in IEEE journals, including 14 papers in IEEE T-IP and 6 papers in IEEE T-PAMI. His publications are well-cited with H-index 55 and 4 of his papers were listed as the top 1% highly cited papers in the academic field of Engineering by Essential Science Indicators. He served as IFS TC Member of IEEE Signal Processing Society, Associate Editor for IEEE SPL, Associate Editor for IEEE T-IP and the founding editorial board member for IET Biometrics. Currently, Dr Jiang is an IEEE Fellow and serves as Senior Area Editor for IEEE T-IP and Editor-in-Chief for IET Biometrics. His current research interests include image processing, pattern recognition, computer vision, machine learning, and biometrics.