Keynote Speakers for ICCIS 2023
ICCIS 2023 Keynote Speakers
Prof. Nasser Kehtarnavaz
Biography: Nasser Kehtarnavaz is an Erik Jonsson Distinguished Professor of Electrical and Computer Engineering at the University of Texas at Dallas. His research areas include signal and image processing, machine learning and deep learning, real-time implementation on embedded processors, and biomedical signal and image analysis. He has authored or co-authored 11 books and more than 400 publications in these areas. Dr. Kehtarnavaz is a Fellow of IEEE, a Fellow of SPIE, a Fellow of AAIA, a licensed Professional Engineer, and has received several awards for his scholarly contributions. He is currently serving as Editor-in-Chief of Springer Journal of Real-Time Image Processing and Chair of SPIE Conference on Real-Time Image Processing and Deep Learning.
Speech Title: Mobile Edge AI: Machine Learning Solutions as Real-Time Smartphone Apps
Abstract: Edge computing solutions are expected to grow substantially during the next few years. This talk first covers the guidelines for turning deep learning models of intelligence into apps running in real-time on smartphones as edge devices. These guidelines are then applied to a real-time signal processing application and a real-time image processing application. The signal processing application involves machine learning-based personalization of the amplification function of hearing aids in an on-the-fly manner. The motivation behind this app is to use smartphones as edge devices to achieve better hearing over standard hearing aid prescriptions in the field or in real-world audio environments. The image processing application involves a deep learning solution to detect diabetic retinopathy in an on-the-fly manner as eye retina images are captured by smartphone cameras fitted with commercially available lenses. The motivation behind this app is to use smartphones as edge devices to conduct cost-effective and widely accessible first-pass eye exams in places with no access to fundus cameras.
Prof. Weisi Lin
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.
Speech Title: Toward QoE Assessment of 3D, Generated and Partially generated Visual Signals
Abstract: There has been significant advancement in 3D visual signal acquisition during recent years, and as a result, 3D visual models, together with computer-generated (artificial) and partially generated visual signals, pave the path to more meaningful visual intelligence, virtual reality (VR), augmented reality (AR), mixed reality (MR), and the emerging metaverse. The proposed talk will start with an introduction of related research and development to acquire and represent 3D visual signals, to model the physical world for AR, MR and metaverse. Since quality of experience (QoE) assessment plays crucial roles in evaluating and shaping related algorithms and systems, we are to substantially present computational models toward QoE for 3D point clouds or meshes, depth-image-based rendering (DIBR), screen content images (SCIs), and so on, to meet various practical requirements. We will then discuss possible future directions, including more comprehensive QoE assessment to consider aesthetics or discomfort factors, and extension to full multimedia (with signals for hearing, touching, and smelling).
Prof. Min Chen
Biography: Min Chen is an IEEE Fellow for his contributions to data-driven communication, caching, and computing. He is a professor in School of Computer Science and Engineering at South China University of Technology. He is the founding Chair of IEEE Computer Society Special Technical Communities on Big Data. He was a professor in School of Computer Science and Technology at Huazhong University of Science and Technology from 2012 to 2022. He was an assistant professor in School of Computer Science and Engineering at Seoul National University since 2009. He worked as a Post-Doctoral Fellow in Department of Electrical and Computer Engineering at University of British Columbia from 2006 to 2009. He received Best Paper Award from IEEE ICC 2012 and IEEE IWCMC 2016, etc. He serves as associate editor for IEEE Transactions on Big Data, IEEE Network, and IEEE Trans. on Cognitive Communications and Networking, etc. He was a Series Editor for IEEE Journal on Selected Areas in Communications. He is Symposium Chair of IEEE Globecom 2022 eHealth, and Co-Chair of IEEE ICC 2012-Communications Theory Symposium, and Co-Chair of IEEE ICC 2013-Wireless Networks Symposium. He was General Co-Chair for IEEE CIT-2012, Tridentcom 2014, Mobimedia 2015, and Tridentcom 2017. He was keynote speaker for IEEE BHI-BSN 2022. He has 300+ publications, including 200+ SCI papers, 100+ IEEE Trans./Journal papers. He has published 12 books, including Big Data Analytics for Cloud/IoT and Cognitive Computing (2017) with Wiley. His Google Scholar Citations reached 39,000+ with an h-index of 93 and i10-index of 296. His top paper was cited 4,100+ times. He was selected as ESI Highly Cited Researcher from 2018 to 2022. He got IEEE Communications Society Fred W. Ellersick Prize in 2017, the IEEE Jack Neubauer Memorial Award in 2019, and IEEE ComSoc APB Oustanding Paper Award in 2022. His research focuses on cognitive computing, 5G Networks, wearable computing, big data analytics, robotics, machine learning, deep learning, emotion detection, and mobile edge computing, etc.
Speech Title: Large Scale Non-Disturbance Sensing and Interactions in 6G Fabric Smart Space
Abstract: In future network, the provisioning of ultra-low latency, non-intrusive and immersive service experience creates various challenges, among which large scale non-disturbance sensing is of great importance to continuously obtain multi-modal information without disturbing user. This talk introduces the development of various functional fabrics, based on which sensing and computing can meet the ultra-reliable and low-latency communication needs of sixth-generation wireless (6G) by integrating sensing units into fabric fibers for multimodal data collections and natural user interactions. Various application examples for human activity capturing are given in 6G fabric smart space.