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X-WR-CALNAME:Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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TZID:Asia/Hong_Kong
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TZOFFSETFROM:+0800
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DTSTART:20240101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20250210T110000
DTEND;TZID=Asia/Hong_Kong:20250210T120000
DTSTAMP:20260510T094634
CREATED:20250210T094548Z
LAST-MODIFIED:20250211T042315Z
UID:108637-1739185200-1739188800@ece.hku.hk
SUMMARY:Advanced Photonic Thin Films and Nanostructures for Next Generation Optoelectronic Systems
DESCRIPTION:Abstract\nPhotonic materials are the backbones of optical communication\, sensing and imaging systems. The advent of artificial intelligence\, internet of things and human-machine interfaces require optical information perception\, data communication and storage with a much higher bandwidth\, smaller footprint yet extremely low power consumption. Bulk materials can no longer support these tasks. Development of advanced photonic thin films and nanostructures becomes the key challenge. In this report\, I will introduce our recent progress on advanced photonic thin films and nanostructures for silicon photonic and free-space optoelectronic systems. I will cover two topics. First\, magneto-optical nonreciprocal photonics for silicon photonics\, including the development of wafer-scale high quality MO thin films\, nanophotonic structures\, nonreciprocal photonic devices and their application in laser module\, silicon photonic FMCW LiDAR systems. Second\, active optical metasurfaces\, including the development of phase change materials\, ferroelectric thin films and optical metasurfaces for optical switching and imaging applications.\n \nSpeaker\nProf. Lei Bi\nProfessor\, Department of Electronic Science and Engineering\,\nUniversity of Electronic Science and Technology of China (UESTC) \nBiography of the Speaker\nLei Bi is a professor in the department of Electronic Science and Engineering of University of Electronic Science and Technology of China (UESTC). He received his B.S. and M.S. degrees in Tsinghua University in 2004 and 2006 respectively\, both majored in materials science. He received his Ph.D. degree in MIT in 2011\, majored in materials science and engineering. He joined UESTC as a professor in 2013. His research interest includes nonreciprocal photonics\, magneto-photonics and optical metasurface. He has authored or co-authored more than 150 papers in peered-viewed journals. He is a senior member of IEEE\, and a member of Optica and SPIE. \nOrganisers\nProf. Han Wang\, Department of Electrical and Electronic Engineering\, HKU\nCenter for Advanced Semiconductors and Integrated Circuits \nAll are welcome!
URL:https://ece.hku.hk/events/20250210-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/02/34343425.jpg
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20250213T143000
DTEND;TZID=Asia/Hong_Kong:20250213T153000
DTSTAMP:20260510T094634
CREATED:20250210T094926Z
LAST-MODIFIED:20250211T042315Z
UID:108642-1739457000-1739460600@ece.hku.hk
SUMMARY:Bridging Minds\, Not Just Devices: Semantic and Goal-Oriented Communication for the Internet of Intelligent Things
DESCRIPTION:Abstract\nThe next frontier of the Internet of Things (IoT) lies in transforming today’s smart devices into collaborative cognitive agents – an ecosystem termed the Internet of Intelligent Things (IoIT). While current IoT systems center on raw data exchange\, they fall short of enabling true collaboration: devices cannot share meaningful insights or align their objectives across dynamic\, real-world tasks. This talk presents a paradigm shift – semantic and goal-oriented communication – as the critical enabler for IoIT. I will introduce a theoretical framework that conceptualizes semantic communication through two key challenges: language exploitation and language design. The language exploitation problem focuses on optimizing the encoding and decoding of semantics to minimize distortion without modifying the underlying semantic language. In contrast\, the language design problem seeks to co-optimize both the encoder and decoder through joint source-channel coding\, particularly leveraging deep learning-based approaches. The talk will also explore the role of large language models in learning adaptive semantic representations\, making communication systems more resilient and context-aware. Finally\, I will discuss how the goal-oriented principle broadens classical Shannon theory by integrating decision-making objectives into communication system design. By framing communication as a meaning-driven\, goal-aware process\, we usher in a new era of collective intelligence – one where smart devices evolve into collaborative cognitive agents capable of shared understanding and coordinated action. \nSpeaker\nDr. Yulin SHAO\nAssistant Professor\, State Key Laboratory of Internet of Things for Smart City\, University of Macau \nBiography of the Speaker\nDr. Yulin Shao is an Assistant Professor with the State Key Laboratory of Internet of Things for Smart City\, University of Macau\, and a Visiting Researcher with the Department of Electrical and Electronic Engineering\, Imperial College London. He received the B.S. and M.S. degrees in Communications and Information Engineering (Hons.) from Xidian University\, China\, in 2013 and 2016\, and the Ph.D. degree in Information Engineering from the Chinese University of Hong Kong in 2020. He was a Research Assistant with the Institute of Network Coding\, a Visiting Scholar with the Research Laboratory of Electronics at Massachusetts Institute of Technology\, a Research Associate with the Department of Electrical and Electronic Engineering at Imperial College London\, and a Lecturer in Information Processing with the University of Exeter. He was a Guest Lecturer at 5G Academy Italy and IEEE Information Theory Society Bangalore Chapter. \nDr. Shao’s research interests include coding and modulation\, machine learning\, and stochastic control. He is a Series Editor of IEEE Communications Magazine in the area of Artificial Intelligence and Data Science for Communications\, an Editor of IEEE Transactions on Communications in the area of Machine Learning and Communications\, and an Editor of IEEE Communications Letters. He received the Best Poster Award at CIE Information Theory Society 2024\, and the Best Paper Awards at IEEE International Conference on Communications (ICC) 2023 and IEEE Wireless Communications and Networking Conference (WCNC) 2024. \nOrganiser\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong
URL:https://ece.hku.hk/events/20250213-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/02/2342544.jpg
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20250213T160000
DTEND;TZID=Asia/Hong_Kong:20250213T170000
DTSTAMP:20260510T094634
CREATED:20250210T095339Z
LAST-MODIFIED:20250211T042315Z
UID:108646-1739462400-1739466000@ece.hku.hk
SUMMARY:6G Waveforms-Perspectives on Throughput\, Reliability\, and ISAC
DESCRIPTION:Online via Zoom link: https://hku.zoom.us/j/2025021302 \nAbstract\nWith the commercialization of 5G technology\, research on 6G has emerged as a key focus in the field of wireless communications. In this talk\, we explore three candidate waveforms for 6G\, designed to meet its stringent requirements for throughput\, reliability\, and integrated sensing and communications (ISAC). \nWe begin by discussing faster-than-Nyquist (FTN) signaling\, a promising technique for enhancing communication spectral efficiency. The unique challenges associated with equalization and channel coding in FTN systems are highlighted\, along with novel solutions that are benchmarked against theoretical performance limits. \nNext\, we examine orthogonal time frequency space (OTFS) modulation\, which enhances communication reliability in dynamic wireless channels. We demonstrate that OTFS introduces a novel coupling mechanism between information symbols and the wireless channel\, enabling efficient equalization and robust MIMO transmissions by fully exploiting channel dynamics. \nFinally\, we focus on a communication-centric ISAC waveform\, evaluating its sensing performance through ambiguity functions. We analytically prove that OFDM is the optimal waveform for minimizing sidelobes in ranging\, while single-carrier waveforms are superior for Doppler sensing when using practical communication signals. \nThe talk concludes with a discussion of potential future research directions in 6G waveform design\, highlighting open challenges and opportunities in this evolving field. \nSpeaker\nDr. Shuangyang Li\nResearch Assistant\, Faculty of Electrical Engineering and Computer Science\, Technical University of Berlin \nBiography of the Speaker\nShuangyang Li (Member\, IEEE) received the B.S.\, M.S.\, and Ph.D. degrees from Xidian University\, China\, in 2013\, 2016\, and 2021\, respectively. He received his second Ph.D. degree from the University of New South Wales (UNSW)\, Australia\, in 2022. He is a recipient of the Marie Skłodowska-Curie Actions (MSCA) fellowship 2022 and is currently a research assistant at the Technical University of Berlin (TU-Berlin). Prior to that\, he was a research associate at the University of Western Australia (UWA). He received the Best Paper Award from IEEE ICC 2023\, and the Best Workshop Paper Award from IEEE WCNC 2023. He was listed in the World’s Top 2% Scientists by Stanford University for citation impact 2024 and is the recipient of the best young researcher award 2024 from the IEEE ComSoc EMEA region. He frequently serves as the organizer/chair for workshops and tutorials on related topics of orthogonal time frequency space (OTFS) in IEEE flagship conferences and is a founding member and currently the co-chair of the special interest group (SIG) on OTFS. He is now an editor of IEEE Transactions on Communications. His research interests include signal processing\, channel coding\, applied information theory\, and their applications to communication systems\, with a specific focus on waveform designs. \nOrganiser\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong
URL:https://ece.hku.hk/events/20250213-2/
LOCATION:Online via Zoom
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/02/23423556.jpg
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20250214T150000
DTEND;TZID=Asia/Hong_Kong:20250214T160000
DTSTAMP:20260510T094634
CREATED:20250210T095554Z
LAST-MODIFIED:20250211T042315Z
UID:108650-1739545200-1739548800@ece.hku.hk
SUMMARY:Ubiquitous Sensing in 6G Cellular Networks
DESCRIPTION:Abstract\nRecently\, the International Telecommunication Union (ITU) has identified integrated sensing and communication (ISAC) as a primary usage scenario for the sixth-generation (6G) cellular networks in IMT-2030 Framework. As a result\, future cellular networks will provide not only communication services\, but also sensing services such as localization and tracking. However\, how to exploit the existing communication infrastructure to effectively achieve sensing functions remains an open problem for 6G. In this talk\, we will introduce the methodologies to leverage various types of communication nodes in cellular networks as anchors\, including base stations\, user equipments\, and intelligent reflecting surfaces\, to perform ubiquitous sensing. Specifically\, the advantages and disadvantages of each type of anchors will be listed\, and the efficient solutions to overcome these disadvantages will be outlined. Apart from theoretical works\, this talk will also present our latest achievements in building a 6G ISAC platform that operates at the millimeter-wave band. We will conclude this talk by discussing some promising future directions that will be beneficial to the transformation of the world’s largest communication network into the world’s largest sensing network. \nSpeaker\nDr. Liang LIU\nAssociate Professor\, Department of Electrical and Electronic Engineering\, The Hong Kong Polytechnic University \nBiography of the Speaker\nLiang Liu is currently an Associate Professor with the Department of Electrical and Electronic Engineering\, The Hong Kong Polytechnic University. He obtained his Ph.D. degree from National University of Singapore in 2014. His research interests lie in 5G/6G technologies\, including integrated sensing and communication (ISAC)\, massive Internet-of-Things (IoT) connectivity\, etc. Currently\, his project about 6G ISAC is supported by the RGC Collaborative Research Fund (CRF) Young Collaborative Research Grant. \nLiang Liu is an IEEE Communications Society (ComSoc) Distinguished Lecturer. He is a recipient of the 2021 IEEE Signal Processing Society (SPS) Best Paper Award\, the 2017 IEEE SPS Young Author Best Paper Award\, the Best Student Paper Award of 2022 IEEE International Conference on Acoustics\, Speech\, and Signal Processing (ICASSP)\, and the Best Paper Award of the 2011 International Conference on Wireless Communications and Signal Processing. He was recognized by Clarivate Analytics as a Highly Cited Researcher in 2018. He is an Editor of IEEE Transactions on Wireless Communications\, and was a Leading Guest Editor of IEEE Wireless Communications Special Issue on Massive Machine-Type Communications for IoT. He is a co-author of the book “Next Generation Multiple Access” published by Wiley-IEEE Press. \nOrganiser\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong
URL:https://ece.hku.hk/events/20250214-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/02/22222355.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20250217T150000
DTEND;TZID=Asia/Hong_Kong:20250217T163000
DTSTAMP:20260510T094634
CREATED:20250211T013747Z
LAST-MODIFIED:20250211T042315Z
UID:108654-1739804400-1739809800@ece.hku.hk
SUMMARY:Personalized Federated Learning and Its Application in 360-degree Video Streaming
DESCRIPTION:Abstract\nFederated learning is a distributed artificial intelligence framework\, which allows multiple edge devices to train a single model collaboratively. In this talk\, we first introduce a personalized federated learning algorithm which can tackle the issues of data heterogeneity and device heterogeneity. Then\, we present a content-based viewport prediction framework for 360-degree video streaming\, wherein users’ head movement prediction models are trained using a personalized federated learning algorithm. The output of the viewport prediction framework corresponds to which video tiles to be transmitted. Finally\, we present an algorithm to determine the bitrate and beamforming matrices in a THz-enabled 360-degree video streaming system with multiple access points. \nSpeaker\nProf. Vincent Wong\nProfessor\nDepartment of Electrical and Computer Engineering\nUniversity of British Columbia\, Canada \nBiography of the Speaker\nVincent Wong is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia\, Vancouver\, Canada. His research areas include protocol design\, optimization\, and resource management of communication networks\, with applications to the Internet\, wireless networks\, smart grid\, mobile edge computing\, and Internet of Things. Dr. Wong is the Editor-in-Chief of the IEEE Transactions on Wireless Communications. He is a Fellow of the IEEE and the Engineering Institute of Canada. \nOrganiser\nProf. Kaibin Huang\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nAll are welcome!
URL:https://ece.hku.hk/events/20250217-1/
LOCATION:Room CB-601J\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/02/1280.jpg
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