Prof. Weisi Lin / IEEE Fellow

Nanyang Technological University, Singapore

Biography: Weisi Lin researches in intelligent image and video processing, computational perceptual signal assessment, and multi-modality/media modeling. He is currently a Professor in School of Computer Science and Engineering, Nanyang Technological University, Singapore, where he also serves as the Associate Chair (Research). He is a Fellow of IEEE and IET, and has been a Highly Cited Researcher 2019, 2020, 2021 and 2022. He has been elected as a Distinguished Lecturer in both IEEE Circuits and Systems Society (2016-17) and Asia-Pacific Signal and Information Processing Association (2012-13), and given keynote/invited/tutorial/panel talks in 40+ international conferences. He has been an Associate Editor for IEEE Trans. Neural Networks and Learning Syst., IEEE Trans. Image Process., IEEE Trans. Circuits Syst. Video Technol., IEEE Trans. Multimedia, IEEE Signal Process. Lett., Quality and User Experience, and J. Visual Commun. Image Represent., and a Senior Editor in APSIPA Trans. Info. and Signal Process, as well as a Guest Editor for 7 special issues in international journals. He also chaired the IEEE MMTC QoE Interest Group (2012-2014); he has been a Technical Program Chair for IEEE ICME 2013, QoMEX 2014, PV 2015, PCM 2012 and IEEE VCIP 2017. He leads the Temasek Foundation Programme for AI Research, Education & Innovation in Asia, 2020-2025. He believes that good theory is practical and has delivered 10+ major systems for industrial deployment with the technology developed.

Title: Opportunities for Visual Computing when Machines Become Ultimate Users of Signals

Up to recently, almost all visual signals (mainly images and videos) captured from the real world have been represented with humans as the targeted ultimate users. Driven by the waves of AI, however, increasingly more visual signals are to have machines as their ultimate users. What opportunities may this shift bring for visual representation and computing? In this speech, models will be firstly discussed to determine visual signal sensitivity and quality toward machine intelligence (MI), e.g., segmentation, classification and location, in comparison with those targeting at human uses. MI-oriented models can be also developed for training-sample generation and identity/privacy protection. Secondly, a possible paradigm change of visual signal representation is explored: intermediate, deep-learnt visual features, instead of whole visual signals, can be the basic unit of representation for MI. This brings intelligence to the edge, and integration of signal representation and computer vision which have been separate processes for long. It can facilitate more accurate feature determination and computation/energy saving as well. Finally, potential research directions will be discussed, including the ultimate differentiation of human intelligence and MI, and extension to full-multimedia modelling (possibly with smell, touch and taste).

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Prof. Yi Huang / IEEE Fellow

University of Liverpool, United Kingdom

Biography: Prof Yi Huang received a BSc in Physics (Wuhan, China), an MSc (Eng) in Microwave Engineering (Nanjing, China), and a DPhil in Communications from the University of Oxford, UK in 1994. He has been conducting research in the areas of antennas, radio propagation, radar, wireless communications, energy harvesting, and applied electromagnetics since 1987. His experience includes 3 years with NRIET (China) as a Radar Engineer and various periods with the Universities of Birmingham, Oxford, and Essex as a member of research staff. He worked as a Research Fellow at British Telecom Labs in 1994 and then joined the Department of Electrical Engineering & Electronics, at the University of Liverpool as a Lecturer in 1995. He was the MS Programme Director and Deputy Head of Department (2015-2023) and is now a Chair in Wireless Engineering and Head of the High-Frequency Engineering Research Group.
Prof Huang has published over 500 refereed papers in leading international journals and conference proceedings and authored books on Antennas: from Theory to Practice (Wiley, 2008, and 2021), and Reverberation Chambers (Wiley 2016, and 2019). He has received over 10 awards (e.g. the IET Premium Award 2022 for Best Paper, EuCAP2023 Best Antenna Paper, the IET Innovation Award 2018, and BAE Systems Chairman's Award 2017) and many research grants from research councils, government agencies, charities, the EU, and industry, acted as a consultant to various companies, and served on many national and international technical committees (such as the IET, EPSRC, European ACE, COST-IC0603, and COST-IC1102, and EurAAP), and been the UK/Ireland Delegate to EurAAP (2016-2020, 2022-2023), an Associate Editor and Guest Editor of four of international journals (including IEEE AWPL 2016-2022), and the Editor-in-Chief of Wireless Engineering and Technology (2014-2023). He has been a keynote/invited speaker and organiser of many international conferences and workshops (e.g. EuCAP, IEEE iWAT, WiCom, and LAPC). He is at present an Associate Editor of IEEE Trans on Antennas and Propagation, a College member of EPSRC, a member of the New Technology Directions Committee and a Distinguished Lecturer of IEEE AP-S, a Senior Fellow of Higher Education Academy (SFHEA), and a Fellow of IEEE (FIEEE).

Title: New and Emerging Directions in Antennas for Mobile Communications

Antennas, as one of the key elements for radio communications, have made significant advancements for the past 50 years, from element antenna, to array and then to the latest MIMO antennas. They have enabled many functions we didn’t expect before. In this talk, I am going to discuss the latest developments and introduce the possible new and emerging directions in the field of antennas for mobile communications.