BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系 - ECPv6.15.20//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系 X-ORIGINAL-URL:https://ece.hku.hk X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系 REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:Asia/Hong_Kong BEGIN:STANDARD TZOFFSETFROM:+0800 TZOFFSETTO:+0800 TZNAME:HKT DTSTART:20240101T000000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250520T140000 DTEND;TZID=Asia/Hong_Kong:20250520T150000 DTSTAMP:20260510T001708 CREATED:20250603T032657Z LAST-MODIFIED:20250603T032657Z UID:111558-1747749600-1747753200@ece.hku.hk SUMMARY:Understanding Complex-Valued Transformer for Modulation Recognition DESCRIPTION:Zoom Link: https://hku.zoom.us/j/95380440070 \nAbstract\nComplex-valued convolution neural networks (CVCNNs) have been recently applied for modulation recognition (MR)\, due to its ability to capture the relationship between the real and imaginary parts of the received signal. On the other hand\, the transformer model has been shown to be distinguished in MR by its superior capability to extract the correlation among high-dimensional signals compared to the CNN. It is a logical next step to ask whether a fully complex-valued transformer based neural network (CVTNN) can bring further performance gain? If so\, where the gain comes from? To answer these questions\, this letter designs the building blocks of the CVTNN for MR\, which is composed of a convolution embedding module\, a complete transformer encoder\, and a C2R classifier\, and establishes the estimation error bound of the proposed CVTNN from an inductive bias perspective. We theoretically prove that the estimation error bound of the proposed CVTNN is lower than that of the real-valued transformer based neural network (RVTNN) for MR. Simulation results further show that the proposed CVTNN outperforms the RVTNN and other benchmarks under different settings\, which corroborates the proposed theoretical analysis. \nSpeaker\nMr. Jingreng Lei\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nSpeaker’s Biography\nJingreng Lei received the B.Eng. degree from Sun Yat-sen University\, China\, in 2023. He is currently working towards MPhil degree with The University of Hong Kong\, Hong Kong. His research interests include complex-valued neural network\, distributed optimization and wireless communication. \nAll are welcome! URL:https://ece.hku.hk/events/20250520-3/ LOCATION:Online via Zoom CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/11/rpg-seminar.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250522T143000 DTEND;TZID=Asia/Hong_Kong:20250522T160000 DTSTAMP:20260510T001708 CREATED:20250603T025446Z LAST-MODIFIED:20250603T025451Z UID:111502-1747924200-1747929600@ece.hku.hk SUMMARY:Reimagining Edge AI and LLM Inference with Compute Memory Architectures DESCRIPTION:Abstract\nRecent advances in artificial intelligence (AI)\, especially in large language models (LLMs)\, have dramatically increased model sizes and computational demands\, significantly straining computing system capabilities. This issue is particularly acute in resource-constrained edge AI scenarios\, where efficient hardware acceleration of compute-intensive tasks and optimization of data reuse to minimize costly data transfers are essential. Addressing these challenges\, this talk will explore various options for designing compute memory subsystems through innovative circuit-level and system-level approaches to enhance the efficiency of edge AI applications. Firstly\, we will introduce MAXWELL\, a near-SRAM co-design computing architecture specifically tailored for edge AI. MAXWELL optimizes performance and energy efficiency by leveraging the regular structure of memory arrays\, achieving high parallelization for both convolutional and fully connected layers\, while supporting fine-grained quantization for real-time image and video processing\, autonomous vehicles\, and Internet of Things (IoT) devices. Secondly\, we will delve into SLIM\, a complementary approach to MAXWELL for big data analytics\, scientific computing\, and financial modeling that provides a cost-effective solution for sparse LLM inference. SLIM leverages in-memory processing in DRAM to significantly reduce latency for large caching datasets in edge AI and utilizes near-storage in Solid State Drives (SSD) for large LLM models. Potential applications of SLIM include. This talk will demonstrate that these complementary approaches for compute memory subsystems can achieve up to 10x speed-ups compared to state-of-the-art edge AI accelerators that require data transfers at the boundaries of ML layers. Furthermore\, the proposed co-design approach can accelerate performance by up to 250x compared to pure software optimizations on the X-HEEP edge AI open-source platform\, which integrates MAXWELL and SLIM logic with a 32-bit RISC-V core. Notably\, these accelerator-specific components of computing memories account for less than 12% of the total memory area of X-HEEP. \nSpeaker\nProf. David ATIENZA\nFull Professor of Electrical and Computer Engineering\,\nHead of the Embedded Systems Laboratory (ESL)\,\nAssociate Vice President for Research Centers and Technology Platforms\,\nÉcole polytechnique fédérale de Lausanne (EPFL)\, Switzerland \nSpeaker’s Biography\nDavid Atienza is a Full Professor of Electrical and Computer Engineering at EPFL\, Switzerland\, where he heads the Embedded Systems Laboratory (ESL) and serves as the Associate Vice President for Research Centers and Technology Platforms. His research focuses on system-level design methodologies for energy-efficient multi-processor system-on-chip (MPSoC) architectures\, targeting next-generation computing servers\, data centers\, and edge AI embedded systems\, particularly smart wearables and medical devices in the Internet of Things (IoT) era. Dr. Atienza has co-authored over 450 publications\, holds 14 patents\, and has received numerous best paper awards at top conferences. He is the Editor-in-Chief of IEEE TCAD and ACM CSUR\, and has served as the Technical Program Chair of DATE 2015 and General Chair of DATE 2017. Among other awards\, he has received the 2024 Test-of-Time Best Paper Award at the IEEE/ACM CODES+ISSS Conference\, the IEEE/ACM ICCAD 10-Year Retrospective Most Influential Paper Award in 2020\, the DAC Under-40 Innovators Award in 2018\, and an ERC Consolidator Grant in 2016. He has also served as President of IEEE CEDA (2018-2019) and Chair of the EDAA (2022-2024). He is a Fellow of IEEE and ACM. \nOrganiser\nProf. Kaibin HUANG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome! URL:https://ece.hku.hk/events/20250522-1/ 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/2025/06/1280-4.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250523T160000 DTEND;TZID=Asia/Hong_Kong:20250523T160000 DTSTAMP:20260510T001708 CREATED:20250603T032424Z LAST-MODIFIED:20250603T032435Z UID:111553-1748016000-1748016000@ece.hku.hk SUMMARY:Security and Efficient Brain-inspired In-memory Computing DESCRIPTION:Zoom Link: https://hku.zoom.us/j/97430126742?pwd=ou6CUPNMjhlrmRbwUKRa8aTHi6PjYX.1\nMeeting ID: 974 3012 6742\nPassword: 967270 \nAbstract\nThe human brain operates as a sophisticated spiking neural network (SNN)\, capable of learning multimodal signals in a zero-shot manner by leveraging prior knowledge. Impressively\, it accomplishes this with minimal energy consumption\, relying on event-driven signals that travel through its intricate structure. However\, replicating the brain’s functionality in efficient neuromorphic hardware poses significant challenges in both hardware and software. Moreover\, training these algorithms demands extensive resources\, and effective security measures remain insufficient. \nBenefiting from the RRAM array inherit stochasticity\, we demonstrated an efficient analogue-digital system that can handle multi-modal spiking signals and possess zero-shot learning capability like a human. This reservoir accelerated system enables significant lower training overheads while maintaining comparable baseline utility. Since emerging brain-inspired computing raises security concerns\, we also share new methodologies insights onto these neuromorphic systems that can secure non-volatile CIM-based parameters without sacrificing latency and energy efficiency. \nThis presentation will delve into the development of a secure and efficient brain-inspired in-memory computing system\, achieved through the integrated co-design of algorithms\, circuits\, and devices. \nSpeaker\nMr. WONG Edwin Kwun Hang\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nSpeaker’s Biography\nMr. Edwin Kwun Hang Wong received the B.Eng. (EE) degree from The University of Hong Kong in 2023. He is currently working towards MPhil degree with The University of Hong Kong. His research interests include AI Security\, Brain-inspired computing\, and RRAM-based accelerator. \nAll are welcome! URL:https://ece.hku.hk/events/20250523-1/ LOCATION:Online via Zoom CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/11/rpg-seminar.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250527T150000 DTEND;TZID=Asia/Hong_Kong:20250527T160000 DTSTAMP:20260510T001708 CREATED:20250603T032119Z LAST-MODIFIED:20250603T032140Z UID:111548-1748358000-1748361600@ece.hku.hk SUMMARY:Digital Over-the-Air Computation: Achieving High Reliability via Bit-Slicing DESCRIPTION:Zoom Link: https://hku.zoom.us/j/99273671426?pwd=bm3VeyFWXnLAlUIBBXJDGAmMfzoKJ5.1 \nAbstract\n6G mobile networks aim to realize ubiquitous intelligence at the network edge via distributed learning\, sensing\, and data analytics. Their common operation is to aggregate high-dimensional data\, which causes a communication bottleneck that cannot be resolved using traditional orthogonal multi-access schemes. A promising solution\, called over-the-air computation (AirComp)\, exploits channels’ waveform superposition property to enable simultaneous access\, thereby overcoming the bottleneck. Nevertheless\, its reliance on uncoded linear analog modulation exposes data to perturbation by noise and interference. Hence\, the traditional analog AirComp falls short of meeting the high-reliability requirement for 6G. Overcoming the limitation of analog AirComp motivates this work\, which focuses on developing a framework for digital AirComp. The proposed framework features digital modulation of each data value\, integrated with the bit-slicing technique to allocate its bits to multiple symbols\, thereby increasing the AirComp reliability. To optimally detect the aggregated digital symbols\, we derive the optimal maximum a posteriori detector that is shown to outperform the traditional maximum likelihood detector. Furthermore\, a comparative performance analysis of digital AirComp with respect to its analog counterpart with repetition coding is conducted to quantify the practical signal-to-noise ratio (SNR) regime favoring the proposed scheme. On the other hand\, digital AirComp is enhanced by further development to feature awareness of heterogeneous bit importance levels and its exploitation in channel adaptation. Lastly\, simulation results demonstrate the achivability of substantial reliability improvement of digital AirComp over its analog counterpart given the same channel uses. \nSpeaker\nMr. Jiawei LIU\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nSpeaker’s Biography\nJiawei Liu received the B.Eng. degree from the Southern University of Science and Technology\, Shenzhen\, China\, in 2020. He is currently pursuing the Ph.D. degree with the Department of Electrical and Electronics Engineering\, The University of Hong Kong (HKU)\, Hong Kong. His research interests include wireless communication system design\, in-memory computing hardware\, and edge intelligence systems. \nAll are welcome! URL:https://ece.hku.hk/events/20250527-1/ LOCATION:Online via Zoom CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/11/rpg-seminar.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250528T143000 DTEND;TZID=Asia/Hong_Kong:20250528T153000 DTSTAMP:20260510T001708 CREATED:20250603T025615Z LAST-MODIFIED:20250626T083737Z UID:111508-1748442600-1748446200@ece.hku.hk SUMMARY:Seminar on Human-AI Ecosystems for Daily Health and Well-being DESCRIPTION:Abstract\nAs the intelligence of everyday smart devices continues to evolve\, they can already monitor basic health behaviors such as physical activities and heart rates. The vision of an intelligent health monitoring and intervention pipeline seems to be within reach. How do we get there? \nIn this talk\, I will introduce a comprehensive pipeline that connects AI\, end-users\, and health experts. For end-users\, I will introduce our work that bridges behavior science theory-driven intervention designs and generalizable behavior models. I will also introduce my efforts on passive sensing datasets\, human-centered algorithms & large language models (LLMs)\, as well as a benchmark platform that drives the community toward more robust and deployable health systems for both end-users and experts. \nSpeaker\nProf. Xuhai (Orson) XU\nAssistant Professor\,\nColumbia University \nSpeaker’s Biography\nXuhai (Orson) XU is an Assistant Professor at Columbia University\, Department of Biomedical Informatics and Department of Computer Science (by courtesy)\, where he directs the SEA (Sense\, Empower\, and Augment) Lab. He is also a visiting faculty researcher at Google. He received his PhD at the University of Washington in 2023 and was a postdoc at MIT until 2024. Specializing in human-computer interaction\, applied machine learning\, and health\, Xu develops deployable behavior modeling algorithms to monitor various health and well-being conditions using everyday sensor data and health records. He further designs and deploys intelligent intervention & interaction techniques that help users achieve personal health and well-being goals and support health experts in making decisions. Xu has earned several awards\, including several Best Paper\, Best Paper Honorable Mention\, and Best Artifact awards. His research has been covered by media outlets such as the Washington Post and ACM News. He was recognized as the Outstanding Student Award Winner at UbiComp 2022\, the 2023 UW Distinguished Dissertation Award\, and the 2024 Innovation and Technology Award at the Western Association of Graduate Schools. \nSEA Lab is actively hiring PhD students with the background of HCI\, mobile sensing\, and applied AI\, with the focus in health applications. \nOrganiser\nProf. Edith C.H. NGAI\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome! URL:https://ece.hku.hk/events/20250528-2/ 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/2025/06/1280-5.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250529T103000 DTEND;TZID=Asia/Hong_Kong:20250529T113000 DTSTAMP:20260510T001708 CREATED:20250603T025752Z LAST-MODIFIED:20250603T025757Z UID:111512-1748514600-1748518200@ece.hku.hk SUMMARY:Seminar on Terahertz Optoelectronics for Non-Invasive Imaging and Beyond DESCRIPTION:Abstract\nTerahertz (THz) imaging technology is growing rapidly due to its potential applications in material exploration\, non-destructive evaluation\, industrial inspection\, and bioinformatics. However\, the practical feasibility of THz imaging systems is significantly constrained by the low efficiency of active THz devices\, long imaging acquisition time\, insufficient use of THz signal datasets\, and their bulky nature. In this talk\, I will present our recent research on high-precision THz imaging systems\, starting from material development\, THz optoelectronics designs\, and system integration toward image reconstruction modalities for on-site applications. As the image data quality and data acquisition speed highly rely on the brightness of THz sources\, we have developed high-performance THz plasmonic photoconductive sources generating mW-level radiating power over a several-THz spectral range\, which offers excellent time-resolved raw data for further image restoration and reconstruction. I will further introduce some of our image reconstruction approaches – equalized compressed sensing imaging\, multi-scale deep-learning fusion imaging\, and compressive hybrid neural network – that further speed up the data acquisition process and achieve significantly better reconstructed imaging quality compared with conventional THz CT modalities. This paves the way toward real-time\, hyperspectral THz 3D imagers in the near future\, which opens the door for various exciting applications in non-destructive sensing\, imaging\, and material inspection. \nSpeaker\nProf. Shang-Hua (Steve) YANG\nAssociate Professor\,\nDepartment of Electrical Engineering\,\nNational Tsing Hua University \nSpeaker’s Biography\nShang-Hua (Steve) YANG is an Associate Professor in the Department of Electrical Engineering at National Tsing Hua University. He is renowned for his significant contributions to THz optoelectronics\, communication\, imaging\, and innovative plasmonic photonics applications. His research findings are published in over 100 refereed papers in peer-reviewed journals and conference proceedings. He has received several prestigious awards\, including the IEEE Antennas and Propagation Society Doctoral Research Award\, MOST Young Scholar Fellowship\, NTHU Young Faculty Research Award\, Human Frontier Science Program Research Grant Award\, and Ta-You Wu Memorial Award (2024). He currently serves as the Director of the NTHU THz Optics & Photonics Center\, Taiwan’s first dedicated THz research center. He is a senior member of IEEE\, Optica\, and SPIE. \nOrganiser\nProf. Kenneth K.Y. WONG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome! URL:https://ece.hku.hk/events/20250529-1/ 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/2025/06/1280-6.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250627T153000 DTEND;TZID=Asia/Hong_Kong:20250627T170000 DTSTAMP:20260510T001708 CREATED:20250619T015442Z LAST-MODIFIED:20250619T015621Z UID:111885-1751038200-1751043600@ece.hku.hk SUMMARY:Seminars on Insights and Best Practices in UK-China Higher Engineering Education DESCRIPTION:Seminar (1): Navigating Excellence in Transnational Engineering Education: The QMUL-BUPT Joint Programme Experience\nSpeaker: Prof. Michael CHAI\, Professor of Internet of Things\, Queen Mary University of London \nAbstract:\nAs global demand grows for engineering graduates equipped with both academic excellence and international perspectives\, transnational education (TNE) plays a vital role in redefining the boundaries of global higher education. This talk presents the strategic vision\, evolution\, and implementation of the Joint Programme (JP)/ Joint Educational Institute (JEI) between Queen Mary University of London and Beijing University of Posts and Telecommunications (QMUL-BUPT)\, a flagship model of collaborative engineering education. \nSince its inception\, the QMUL-BUPT JP has been committed to delivering a world-class\, research-informed curriculum that bridges Eastern and Western educational philosophies while upholding rigorous UK academic standards. The programme not only cultivates technical expertise but also fosters global competence\, bilingual communication skills\, and intercultural understanding. Central to its success are shared academic governance\, faculty exchange\, quality assurance mechanisms\, and ongoing innovation in teaching and assessment. \nThis talk will highlight how the programme has evolved to meet the changing needs of students and industry. Attendees will gain insights into the opportunities and challenges of sustaining excellence in TNE and the strategic leadership required to foster impactful global academic partnerships. \n******************************************************************* \nSeminar (2): Shaping AI-Ready Graduates through Higher Education Innovation\nSpeaker: Prof. Yue CHEN\, Professor of Telecommunications Engineering\, Queen Mary University \nAbstract:\nAs Artificial Intelligence (AI) transforms the global workforce and the landscape of higher education\, preparing students with AI competence has become both a strategic imperative and a pedagogical challenge. This talk introduces AICoDE\, a structured and human-centred framework\, recently developed and implemented at Queen Mary University of London and Beijing University of Posts and Telecommunications (QMUL-BUPT) joint transnational education programmes. \nAICoDE is designed to formally embed AI competence development into the engineering curriculum. It pursues three key objectives: to leverage AI’s transformative potential to enrich teaching and learning; to mitigate the risks associated with its misuse or unethical application; and to equip graduates with the critical knowledge and skills required to thrive in increasingly AI-driven professional environments. \nA distinctive feature of AICoDE is its 3A assessment strategy\, which scaffolds AI integration in education while safeguarding academic integrity and promoting critical thinking. This talk will also outline the framework’s implementation through curriculum and assessment mapping. Attendees will gain strategic insights and actionable guidance on embedding AI literacy and competence into higher education curricula\, with relevance across both institutional and international contexts. \n*******************************************************************\nSpeakers’ Biography: \nProf. Michael CHAI is Professor of Internet of Things at the School of Electronic Engineering and Computer Science\, Queen Mary University of London. He serves as the Queen Mary Director of TNE in partnership with BUPT in Beijing. His research began in smart Internet of Things and wireless communications\, and has since expanded to include pedagogical scholarship aimed at enhancing student learning and academic development in Higher Education and transnational contexts. \nProf. Yue CHEN is Professor of Telecommunications Engineering\, Director of Scholarship\, and Senior Advisor for Transnational Education at the School of Electronic Engineering and Computer Science\, Queen Mary University of London. She is an accomplished academic whose work bridges technical expertise and educational innovation\, with a focus on wireless communications\, mobile edge computing\, and the Scholarship of Teaching and Learning. Her current research and leadership activities centre on active learning\, curriculum enhancement\, the pedagogical integration of AI in higher education\, and the advancement of transnational education. \nOrganiser: Prof. Yuanwei LIU\, Professor\, Department of Electrical and Electronic Engineering\, HKU \nAll are welcome! URL:https://ece.hku.hk/events/20250627-1/ 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/2025/06/1280-7.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250709T160000 DTEND;TZID=Asia/Hong_Kong:20250709T170000 DTSTAMP:20260510T001708 CREATED:20250707T114033Z LAST-MODIFIED:20250708T020744Z UID:112581-1752076800-1752080400@ece.hku.hk SUMMARY:Seminar on AI for 6G Communications DESCRIPTION:Abstract\nIntelligent reflecting surface (IRS) is envisioned to be a promising 6G technology which changes wireless communications from “adapting to wireless channels” to “changing wireless channels”. However\, current IRS configuration schemes\, consisting of sub-channel estimation and passive beamforming\, are model-based designs and are difficult to be realized in practical and complex radio environment. To create the smart radio environment\, we propose a model-free design of IRS control that is independent of the sub-channel channel state information (CSI) and requires the minimum interaction between IRS and the wireless communication system. We firstly model the control of IRS as a Markov decision process (MDP) and apply deep reinforcement learning (DRL) to perform real-time coarse phase control of IRS. Radio map technology offers a refined solution to reduce MIMO beamforming’s dependency on channel state information (CSI). We introduce a deep learning-based approach to generate radio maps directly from raw CSI data of MIMO systems\, presenting two baseline schemes—one predictive and another based on throughput. An end-to-end architecture\, tailored to MIMO beamforming vectors from location data\, is proposed to employ deep neural networks through a task-oriented design and a customized loss function. Our numerical results highlight the advantages of this approach\, suggesting the potential to replace MIMO CSI with location data. \nSpeaker\nProf. Wei ZHANG\nProfessor\,\nSchool of Electrical Engineering and Telecommunications\,\nThe University of New South Wales\nVice President\, IEEE Communications Society \nSpeaker’s Biography\nWei Zhang (F’15) is Vice President of IEEE Communications Society. He received the Ph.D. degree from the Chinese University of Hong Kong in 2005. Currently\, he is a professor at the School of Electrical Engineering and Telecommunications\, the University of New South Wales\, Sydney\, Australia. His current research interests include 6G communications. He has been an IEEE Fellow since 2015 and was an IEEE ComSoc Distinguished Lecturer in 2016-2017. Within the IEEE ComSoc\, he has taken many leadership positions including Chair of Wireless Communications Technical Committee (2019-2020)\, Vice Director of Asia Pacific Board (2016-2021)\, Editor-in-Chief of IEEE Wireless Communications Letters (2016-2019)\, Member-at-Large on the Board of Governors (2018-2020)\, Technical Program Committee Chair of APCC 2017 and ICCC 2019 and 2024\, Award Committee Chair of Asia Pacific Board and Award Committee Chair of Technical Committee on Cognitive Networks. \nOrganiser\nProf. Kaibin HUANG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome! URL:https://ece.hku.hk/events/20250709-1/ 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/2025/07/1280.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250715T160000 DTEND;TZID=Asia/Hong_Kong:20250715T170000 DTSTAMP:20260510T001708 CREATED:20250709T033608Z LAST-MODIFIED:20250709T033659Z UID:112605-1752595200-1752598800@ece.hku.hk SUMMARY:Seminar on 6G Wireless Enabled Autonomous Driving and Transportation of Future DESCRIPTION:Abstract\nThe forthcoming sixth generation (6G) wireless networks will be one of the galvanizing technologies for future advanced and autonomous transportation systems. 6G wireless will provide communication services with stringent requirements which are necessary for autonomous driving and on-flight Internet connectivity. Introduction of AI-empowered 6G would guarantee a more intelligent\, efficient and secure transportation system. In this talk\, some of the new usage scenarios and capabilities of the 6G compared with the existing cellular networks will be outlined\, followed by description of its potential and challenges for seamless and ubiquitous connectivity across the heterogeneous and multi-layer transportation systems. \nSpeaker\nProf. Abbas JAMALIPOUR\nPhD\, Fellow IEEE\, Fellow IEICE\, Fellow IEA\, Fellow AIIA\nChair Professor of Ubiquitous Mobile Networking\, The University of Sydney\nEditor-in-Chief\, IEEE Transactions on Vehicular Technology\nPast President\, IEEE Vehicular Technology Society \nSpeaker’s Biography\nProf. 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 IEEE\, IEICE\, Engineers Australia\, AIIA\, and a Visiting Fellow of the Royal Academy of Engineering. He has authored nine technical books\, eleven book chapters\, over 650 technical papers\, and five patents\, all in the field of wireless communications. He 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\, member of the Advisory Board of IEEE Internet of Things Journal\, and an editor for several other journals. He is the recipient of several prestigious awards such as the IEEE ComSoc Harold Sobol Award\, the IEEE ComSoc Best Tutorial Paper Award\, as well as over fifteen Best Paper Awards. \nOrganiser\nProf. Hongyang DU\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong URL:https://ece.hku.hk/events/20250715-1/ 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/2025/07/1280-1.jpg END:VEVENT BEGIN:VEVENT DTSTART;VALUE=DATE:20250719 DTEND;VALUE=DATE:20250720 DTSTAMP:20260510T001708 CREATED:20250326T030136Z LAST-MODIFIED:20250625T063840Z UID:110671-1752883200-1752969599@ece.hku.hk SUMMARY:HKU-EEE RoboLeague 2025 港大電機電子工程：中學機械人競技聯盟2025 DESCRIPTION:🚀 Join the Excitement of Robotics! \nCompetition Details\nDate: 19 July 2025 (SAT)\nTime: Check-in begins at 9:00 AM\nVenue: Innovation Wing One\, G/F\, Hui Oi Chow Science Building\, The University of Hong Kong (HKU) (directions to the venue) \nCompetition Description\nEngage your autonomous robots in thrilling challenges:\n– Maze Navigation 迷宮探索 ​\n– Rescue Missions 搜救任務 ​\n– Soccer League – Standard Platform 足球標準平台組 ​\n– Soccer League – Open Platform 足球公開組 ​ \nWho Can Join?\nTarget Audience: Secondary School Students Team Formation: No more than 4 students ( any Forms ) per team from the same school \nKey Dates\n*Briefing Session: \n– Date: 26 April 2025 (SAT) @11:00AM \n– Venue: Room 603\, 6/F\, Chow Yei Ching Building\, HKU \n*Application Deadline: \n– Date: 30 April 2025 (WED) @11:59PM \nRegistration & Details\nhttps://linktr.ee/hkeeerl URL:https://ece.hku.hk/events/20250426-1/ LOCATION:Tam Wing Fan Innovation Wing One\, G/F\, Hui Oi Chow Science Building\, The University of Hong Kong (HKU) CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/03/banner.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250724T143000 DTEND;TZID=Asia/Hong_Kong:20250724T153000 DTSTAMP:20260510T001708 CREATED:20250722T064431Z LAST-MODIFIED:20250722T064800Z UID:112757-1753367400-1753371000@ece.hku.hk SUMMARY:Seminar on Symmetric Diffusers: Learning Discrete Diffusion on Finite Symmetric Groups DESCRIPTION:Abstract\nFinite symmetric groups Sn are essential in fields such as combinatorics\, physics\, and chemistry. However\, learning a probability distribution over Sn poses significant challenges due to its intractable size and discrete nature. We introduce SymmetricDiffusers\, a novel discrete diffusion model that simplifies the task of learning a complicated distribution over Sn by decomposing it into learning simpler transitions of the reverse diffusion using deep neural networks. We identify the riffle shuffle as an effective forward transition and provide empirical guidelines for selecting the diffusion length based on the theory of random walks on finite groups. Additionally\, we propose a generalized Plackett-Luce (PL) distribution for the reverse transition\, which is provably more expressive than the PL distribution. We further introduce a theoretically grounded “denoising schedule” to improve sampling and learning efficiency. Extensive experiments show that our model achieves state-of-the-art or comparable performances on solving tasks including sorting 4-digit MNIST images\, jigsaw puzzles\, and traveling salesman problems. \nSpeaker\nProf. Renjie LIAO\nDepartment of Electrical and Computer Engineering\, and\nDepartment of Computer Science\,\nUniversity of British Columbia (UBC) \nSpeaker’s Biography\nRenjie Liao is an Assistant Professor in the Department of Electrical and Computer Engineering and an Associate Member of the Department of Computer Science at the University of British Columbia (UBC). He is also a faculty member at the Vector Institute and holds a Canada CIFAR AI Chair. Prior to joining UBC\, he was a Visiting Faculty Researcher at Google Brain\, working with Geoffrey Hinton and David Fleet. He received his Ph.D. in Computer Science from the University of Toronto in 2021\, under the supervision of Richard Zemel and Raquel Urtasun. During his Ph.D.\, he also worked as a Senior Research Scientist at Uber Advanced Technologies Group. He holds an M.Phil. in Computer Science from the Chinese University of Hong Kong (2015) and a B.Eng. in Automation from Beihang University (2011). His research interests span machine learning and its intersection with computer vision\, self-driving\, healthcare\, and beyond\, with a particular focus on probabilistic and geometric deep learning. \nOrganiser\nProf. Xiaojuan QI\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome! URL:https://ece.hku.hk/events/20250724-1/ 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/2025/07/1280-2.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250808T140000 DTEND;TZID=Asia/Hong_Kong:20250808T160000 DTSTAMP:20260510T001708 CREATED:20250801T021445Z LAST-MODIFIED:20250804T020549Z UID:112825-1754661600-1754668800@ece.hku.hk SUMMARY:Seminar on Publishing in Nature Nanotechnology: An insider’s view of Nature journals DESCRIPTION:Abstract\nDr. Lu will talk about the scope of Nature Nanotechnology and an overview of Nature journals. And she will share her experience on the editorial process (the workflow and the statistical data) and disclose the criteria of Nature journals from an insider’s view. Through the talk\, you will know better on what kind of papers a highly selective journal is looking for\, how the editors decide whether to send a paper out or not\, what they will do when the reviewers’ comments are contradictory. And Lu is happy to share with you her personal experience as an editor if you are interested together with some practical tips for writing and submitting a paper to a Nature journal. \nSpeaker\nDr. Lu Shi\nSenior Editor\nSpringer Nature \nSpeaker’s Biography\nDr. Lu Shi joined Nature Nanotechnology in April 2023 from Wiley\, where she was the Editor-in-Chief of Advanced Electronic Materials and Deputy Editor of Advanced Materials. Prior to her editorial career\, she worked on 2D materials growth and magnetoelectric transport behavior of van der Waals heterostructures. For her work\, she received a joint PhD in Materials Science and Physics from the Université Catholique de Louvain\, Belgium and Université Grenoble Alpes\, France. She obtained her BEng and MSc in Materials Science and Engineering from Shanghai Jiao Tong University and Shanghai Institute of Ceramics\, Chinese Academy of Sciences. She covers a broad range of topics across electronics and optoelectronics in the journal and is based in Shanghai. \nOrganiser\nProf. Can Li\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome! URL:https://ece.hku.hk/events/20250808-1/ LOCATION:Tam Wing Fan Innovation Wing Two\, G/F\, Run Run Shaw Building\, The University of Hong Kong CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/08/Can-Li_20250808-seminar-web-banner.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250814T160000 DTEND;TZID=Asia/Hong_Kong:20250814T173000 DTSTAMP:20260510T001708 CREATED:20250813T012141Z LAST-MODIFIED:20250813T013434Z UID:113006-1755187200-1755192600@ece.hku.hk SUMMARY:Seminar on Voltage Stability Constrained Power System Optimization: A Constraint-learning Method DESCRIPTION:Abstract\nHigh penetration of renewable energy poses severe challenges to power system voltage stability due to weakened voltage and reactive power support\, complex voltage stability mechanisms\, and highly diversified operation states. Traditional control strategies predefined based on limited operation states fail to maintain the required voltage stability margin. This report presents a constraint-learning-based framework for embedding accurate and efficient voltage stability constraints into power system optimization to improve voltage stability of the optimization results. The proposed framework represents the inherently nonlinear and nonconvex voltage stability constraints using multiple convex polyhedrons (MCPH). The learned constraints are linear\, sparse\, and embeddable in mixed-integer linear programming (MILP) formulations. Case studies demonstrate that integrating MCPH constraints into voltage stability constrained unit commitment improves voltage stability margin with reduced computational burden. Furthermore\, the framework is extended to generation expansion planning\, where physical ensemble constraint learning captures converter-driven stability requirements across diverse generation mix scenarios. The results confirm that the proposed approach effectively balances stability enhancement\, solution efficiency\, and scalability for high-renewable\, stability-constrained power system optimization. \nSpeaker\nMr. Hongyang Jia\nTsinghua University \nSpeaker’s Biography\nHongyang Jia received the B.S. degree in electrical engineering in 2021 from Tsinghua University\, Beijing\, China\, where he is currently pursuing the Ph.D. degree in Electrical Engineering under the supervision of Associate Prof. Ning Zhang. He was a Visiting Ph.D. Student at Imperial College London (Aug. 2024 – Feb. 2025) under Associate Prof. Fei Teng. His research interests center on trustworthy machine learning for science and engineering\, with specific applications in power system optimization under voltage stability constraints\, data-driven security/stability rule extraction and embedding\, and power system voltage stability assessment. \nOrganiser\nProf. Wang Yi \nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome! URL:https://ece.hku.hk/events/20250814-1/ LOCATION:Room CB-601J\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=application/pdf:https://ece.hku.hk/wp-content/uploads/2025/08/August-14-2025-1-Web-banner.pdf END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250815T110000 DTEND;TZID=Asia/Hong_Kong:20250815T120000 DTSTAMP:20260510T001708 CREATED:20250806T043442Z LAST-MODIFIED:20250806T090812Z UID:112883-1755255600-1755259200@ece.hku.hk SUMMARY:Seminar on Towards Deep Learning MR Reconstruction with No Ground Truth and Fast Inference DESCRIPTION:Abstract\nSince 2016\, deep learning techniques have been introduced to solve the inverse problem of MR image reconstruction from undersampled data from accelerated acquisitions. Since then\, the field has grown substantially. A wide range of machine learning methods have been developed\, translated into clinical practice and adopted as products by all major scanner vendors. In this talk\, after a general introduction to deep learning for MR image reconstruction\, I will focus on two open challenges in the field. First\, the application of deep learning reconstruction for dynamic contrast-enhanced imaging and abdominal imaging\, where no ground truth can be obtained for model training. Second\, the optimisation of network architectures towards computation time at inference for real-time imaging and clinical translation of instance-specific learning\, where trainings need to be performed during inference. \nSpeaker\nProf. Florian KNOLL\nProfessor and Head of the Computational Imaging Lab\,\nDepartment Artificial Intelligence in Biomedical Engineering (AIBE)\,\nFriedrich-Alexander-Universität Erlangen-Nürnberg \nSpeaker’s Biography\nProf. Florian KNOLL received his PhD in Electrical Engineering in 2011 from Graz University of Technology. From 2015 to 2021\, he was Assistant Professor for Radiology at the Center for Biomedical Imaging at NYU Grossman School of Medicine. Since 2021\, he has been Professor and Head of the Computational Imaging Lab at the Department Artificial Intelligence in Biomedical Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg. He currently holds four grants from the German Research Fund (DFG) and an R01 grant from the National Institutes of Health (NIH). His research interests include iterative MR image reconstruction\, parallel MR imaging\, compressed sensing and machine learning. \nOrganiser\nProf. Ed Xuekui WU\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome! URL:https://ece.hku.hk/events/20250815-1/ 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/2025/08/1280.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250905T093000 DTEND;TZID=Asia/Hong_Kong:20250905T103000 DTSTAMP:20260510T001708 CREATED:20250902T061920Z LAST-MODIFIED:20250902T091613Z UID:113160-1757064600-1757068200@ece.hku.hk SUMMARY:Seminar on Illuminating Life Sciences: Optical Engineering Technologies for Neuroscience and Biology DESCRIPTION:Abstract\nIn this talk\, the speaker will introduce how optical technology can contribute to biological studies. Light has long been one of the most powerful tools for investigating living systems. Optical imaging techniques allow direct observation of dynamic cellular processes in vivo\, while optogenetics enables the precise modulation of neuronal circuits with high spatiotemporal resolution. \nIn Part One\, the speaker will present how digital micromirror device (DMD) equipped beam projection technology\, commonly used in movie theatres\, can be adapted for functional mapping of the mouse brain. In Part Two\, the speaker will describe how liquid crystal display (LCD) technology enables ultrafast optical recording of neuronal circuit activity. Finally\, in Part Three\, the speaker will outline my current and future research directions in immunophotonics\, driven by large-scale optical imaging\, deep learning–assisted automated cell tracking\, and skull transparency techniques for real-time visualisation of brain–immune system interactions. \nSpeaker\nDr. Seonghoon KIM\nSenior Research Scientist\,\nDepartment of Automation\,\nTsinghua University \nSpeaker’s Biography\nSeonghoon KIM is a Senior Research Scientist in the Department of Automation at Tsinghua University. He received his Ph.D. from the Korea Advanced Institute of Science and Technology (KAIST) in South Korea and subsequently completed postdoctoral training at Harvard Medical School\, Seoul National University\, and Tsinghua University. His research background is exceptionally broad\, spanning materials science\, optics\, neuroscience\, computational science\, and immunology. For example\, he has studied the oxidation of nanocrystal metal films\, developed implantable biomaterials\, developed photodynamic therapy for cancer treatment\, applied optogenetics with fMRI for functional mapping of the mouse brain\, and developed an ultrafast optical imaging system for neuronal voltage imaging. Recently\, he has published several papers in leading journals\, including Neuron\, Nature Communications\, Advanced Materials\, and Nature Methods. His current research focuses on investigating in vivo biological dynamics—particularly in neuroscience and immunology— through large-scale optical imaging systems integrated with computational imaging techniques.\n\nAll are welcome! URL:https://ece.hku.hk/events/20250905-1/ 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/2025/09/1280-1.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250910T141500 DTEND;TZID=Asia/Hong_Kong:20250910T163000 DTSTAMP:20260510T001708 CREATED:20250806T033603Z LAST-MODIFIED:20250827T025141Z UID:112877-1757513700-1757521800@ece.hku.hk SUMMARY:William Mong Distinguished Lecture cum Workshop – Unlocking MIMO in 6G: The Evolution of MIMO in Cellular Systems DESCRIPTION:All members of the HKU community and the general public are welcome to join. Seats for on-site participants are limited. Interested parties please register through the link below by September 9\, 2025 18:00pm:https://hkuems1.hku.hk/hkuems/ec_hdetail.aspx?guest=Y&ueid=102594  \nA confirmation email will be sent to participants who have successfully registered. \nAbstract\nWireless networks have fundamentally transformed our daily lives. Behind this revolution\, Multiple-Input Multiple-Output (MIMO) communication standing out as one of the most influential innovations. By spatially multiplexing data streams across different antennas\, MIMO enables high-rate access. In this talk\, Professor Heath will introduce the fundamentals of MIMO communication and explore its applications within cellular systems. The lecture will begin with an overview of single-user and multi-user MIMO\, highlighting their pivotal role in 4G networks. It will then discuss the adaptation of MIMO techniques to 5G millimeter-wave systems. Finally\, the talk will explore a forward-looking concept: the tri-hybrid MIMO architecture\, which integrates reconfigurable antennas into digital/analog hybrid MIMO framework to support very large-scale antenna arrays. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Keynote Speaker:\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Professor Robert Wendell Heath Jr.University of California San Diego \n \n \n \n \n \n Biography\nProfessor Robert W. Heath Jr. is the Charles Lee Powell Chair in Wireless Communication in the Department of ECE at the University of California San Diego.  He is the recipient or co-recipient of several awards including the 2019 IEEE Kiyo Tomiyasu Award\, the 2020 North Carolina State University Innovator of the Year Award\, the 2021 IEEE Vehicular Technology Society James Evans Avant Garde Award\, and the 2025 IEEE/RSE James Clerk Maxwell Medal. He authored “Introduction to Wireless Digital Communication” (Prentice Hall in 2017) and “Digital Wireless Communication: Physical Layer Exploration Lab Using the NI USRP” (National Technology and Science Press in 2012). He co-authored “Millimeter Wave Wireless Communications” (Prentice Hall in 2014) and “Foundations of MIMO Communications” (Cambridge 2019). He is a licensed Amateur Radio Operator\, a registered Professional Engineer in Texas\, a Private Pilot\, a Fellow of the National Academy of Inventors\, a Fellow of the IEEE\, and a Fellow of the AAAS. He is an elected member of the United States National Academy of Engineering\, 2025 class. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Panellists:\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Professor Nuria González PrelcicUniversity of California San Diego \n \n \n \n \n \n Biography\nProfessor Nuria González Prelcic received her Ph.D. with Honors in 2000 from the University of Vigo\, Spain. She is a Professor at the ECE Department of the University of California San Diego since January 2024. Her main research interests include signal processing and machine learning for wireless communications. She has published more than 150 papers in these areas\, including a highly cited tutorial on signal processing for mmWave MIMO published in the IEEE Journal of Selected Topics in Signal Processing which has received the 2020 IEEE SPS Donald G. Fink Overview Paper Award\, and a paper pioneering the idea of enabling automotive radar with a WiFi waveform that won the 2022 IEEE Vehicular Technology Society Best Vehicular Electronics Paper Award. She has been an Editor for IEEE Transactions on Wireless Communications and IEEE Transactions Communications. She is a member of the IEEE Signal Processing Society TWG on Integrated Sensing and Communication\, SPCOM Technical Committee and IEEE SPS Education Board. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Dr Peiying ZhuHuawei \n \n \n \n \n \n Biography\nDr Peiying Zhu\, Senior Vice President of Wireless Research\, is a Huawei Fellow\, IEEE Fellow and Fellow of Canadian Academy of Engineering. She is currently leading 6G wireless research and standardization in Huawei. The focus of her research is advanced radio access technologies. She is actively involved in 3GPP and IEEE 802 standards development. She has been regularly giving talks and panel discussions on 5G/6G vision and enabling technologies. She led the team to contribute significantly to 5G technologies and standardization. Many technologies developed by the team have been adopted into 5G standards and implemented in 5G products. She served as the guest editor for IEEE Signal processing magazine special issue on the 5G revolution and IEEE JSAC on Deployment Issues and Performance Challenges for 5G. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Professor Zhisheng NiuTsinghua University \n \n \n \n \n \n Biography\nProfessor Zhisheng Niu graduated from Beijing Jiaotong University\, China\, in 1985\, and got his M.E. and D.E. degrees from Toyohashi University of Technology\, Japan\, in 1989 and 1992\, respectively.  During 1992-1994\, he worked for Fujitsu Laboratories Ltd.\, Japan\, and in 1994 joined with Tsinghua University\, Beijing\, China\, where he is now a professor at the Department of Electronic Engineering. During 1997-1998\, he visited Hitachi Central Research Laboratory as a HIVIPS senior researcher.  His major research interests include queueing theory and traffic engineering\, wireless communications and mobile Internet\, vehicular communications and smart networking\, and green communication and networks. Professor Niu has been serving IEEE Communications Society since 2000\, first as Chair of Beijing Chapter and then as Director of Asia-Pacific Board\, Director for Conference Publications\, Chair of Emerging Technologies Committee\, Director for Online Contents\, Editor-in-Chief of IEEE Trans. Green Commun. & Networks\, and currently Chair of Emerging Technologies Committee.  He received the Distinguished Technical Achievement Recognition Award from IEEE Communications Society Green Communications and Computing Technical Committee in 2018.  He was selected as a distinguished lecturer of IEEE Communication Society as well as IEEE Vehicular Technologies Society.  He is a fellow of both IEEE and IEICE. \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Professor Chan Byoung ChaeYonsei University \n \n \n \n \n \n Biography\nProfessor Chan Byoung Chae received the Ph.D. degree in electrical and computer engineering from The University of Texas at Austin (UT) in 2008. Prior to joining UT\, he was a Research Engineer at the Telecommunications Research and Development Center\, Samsung Electronics\, Suwon\, South Korea\, from 2001 to 2005. He is currently an Underwood Distinguished Professor and Lee Youn Jae Fellow (Endowed Chair Professor) with the School of Integrated Technology\, Yonsei University\, South Korea. Before joining Yonsei University\, he was with Bell Labs\, Alcatel-Lucent\, Murray Hill\, NJ\, USA\, from 2009 to 2011\, as a Member of Technical Staff\, and Harvard University\, Cambridge\, MA\, USA\, from 2008 to 2009\, as a Post-Doctoral Research Fellow. He was the Editor-in-Chief of IEEE Trans. Molecular\, Biological\, and Multi-scale Communications. He was an IEEE ComSoc Distinguished Lecturer from 2020 to 2023 and is an IEEE VTS Distinguished Lecturer from 2024 to 2025. He is an elected member of the National Academy of Engineering of Korea. URL:https://ece.hku.hk/events/20250910-1/ LOCATION:Rayson Huang Lecture Theatre\, The University of Hong Kong (HKU) CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/08/1280-2.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250911T113000 DTEND;TZID=Asia/Hong_Kong:20250911T123000 DTSTAMP:20260510T001708 CREATED:20250828T043420Z LAST-MODIFIED:20250904T022125Z UID:113136-1757590200-1757593800@ece.hku.hk SUMMARY:AI Career Journey with Fano DESCRIPTION:About the Talk\nArtificial Intelligence (AI) is revolutionising industries\, and speech recognition stands at the forefront of this transformation. In this engaging session\, we will delve into the fascinating world of AI\, focusing on speech recognition and its related technologies with incredible potential. Fano will share insights from our journey—how they navigated the challenges and innovations in speech recognition\, from building cutting-edge models to addressing real-world applications. Learn about the skills\, tools\, and mindset required to excel in this niche\, as well as the exciting opportunities in this growing domain. \nThis talk will showcase Fano’s use cases and innovations in speech recognition that are shaping industries\, and cover the topic of the exciting career opportunities in AI and speech technologies\, and how to get started. Whether you’re a student\, postdoc or researcher curious about the world of AI and speech technologies\, this talk will inspire and equip you to take the next step in your own career journey. \nSpeaker\nIr. Dr. Albert LAM\, Chief Research Officer at Fano \nSpeaker’s Biography\nAlbert LAM received his BEng degree with First Class Honours in Information Engineering from The University of Hong Kong\, Hong Kong\, in 2005\, and he obtained his PhD degree at the Department of Electrical and Electronic Engineering of HKU in 2010. He was a postdoctoral scholar at the Department of Electrical Engineering and Computer Sciences of the University of California\, Berkeley. He was a Research Assistant Professor at the Department of Computer Science of Hong Kong Baptist University from 2012 to 2015 and the Department of Electrical and Electronic Engineering (EEE) of HKU in 2015–17. He is now the Chief Research Officer at Fano\, a deep-tech startup specialising in speech and language technologies. He also serves as an Adjunct Associate Professor at HKU. He is a Croucher Research Fellow. He is one of the top 2% scientists Worldwide by Stanford University\, 2020–24. He is a member of the Expert Committee of the Shenzhen Artificial Intelligence Industry Association. His research interests include optimisation theory and algorithms\, artificial intelligence\, evolutionary computation\, smart grids\, and smart cities. He is a Senior Editor of  IEEE Transactions on Intelligent Transportation Systems\, an Associate Editor of IEEE Transactions on Evolutionary Computation\, IEEE Transactions on Artificial Intelligence\, and IEEE Transactions on Emerging Topics in Computational Intelligence. He is also the Editor-in-Chief of EAI Endorsed Transactions on Energy Web. \nSupported By URL:https://ece.hku.hk/events/20250911-1/ LOCATION:Tam Wing Fan Innovation Wing Two\, G/F\, Run Run Shaw Building\, The University of Hong Kong CATEGORIES:Career Talks,Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/08/1280-1.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250916T103000 DTEND;TZID=Asia/Hong_Kong:20250916T123000 DTSTAMP:20260510T001708 CREATED:20250829T070951Z LAST-MODIFIED:20250909T084555Z UID:113143-1758018600-1758025800@ece.hku.hk SUMMARY:HKU Centennial Distinguished Chinese Scholars Scheme – Public Lecture: Theory\, Technology and Engineering Practice in the Evolution of Mobile Communications (移动通信演进中的理论、技术及工程实践) DESCRIPTION:Registration Link: https://hkuems1.hku.hk/hkuems/ec_hdetail.aspx?guest=Y&ueid=102673 \nKindly note that the lecture will be conducted in Putonghu. \nSpeaker\nProf. Ping ZHANG\, Beijing University of Posts and Telecommunications \nAbstract\nSyntactic communication is marked by the American scientist Shannon Information Theory\, which points out the development direction for information measurement\, compression and transmission. However\, after nearly 80 years of development\, syntactic communication has entered a bottleneck. First\, the contradiction between chip size and component scale in the post-Moore era is becoming more and more prominent\, and the limitations brought about by von Neumann’s structure are becoming more and more obvious. Second\, it can be seen from the Shannon channel capacity formula that although increasing physical dimensions such as antennas\, spectrum\, and power can improve system capacity\, it consumes huge resources and is difficult to sustainable. Third\, new communication objects such as different types of robots are emerging\, which are very different from human communication needs and information reception methods. Therefore\, disruptive innovation is needed to realise new requirements! \nThis report expounds the changes brought about by this innovation from the basic theory\, core methods\, design ideas and other aspects. As a new communication paradigm\, semantic communication subverts the traditional communication technology system\, opens up innovative technical ways for the integration of communication and intelligence\, and has made breakthroughs in three aspects: basic theoretical research\, core technology research\, and engineering test verification. At present\, it is becoming more and more widely recognised by the industry and peers. Finally\, this report confirms that semantic communication is indeed the “inflection point” technology of 6G from the perspective of engineering experiment verification\, proving that AI can be integrated with wireless communication to efficiently overcome the “last mile” problem of knowledge and model network transmission. The breakthrough of semantic communication has brought about a change in the design of traditional communication systems\, which is no longer an innovation that adopts traditional extension line fragmentation in intergenerational evolution\, but adopts powerful AI and communication system modular\, low-cost\, and explainable optimisation fusion\, and obtains huge gains in the performance of the fusion system. \nSpeaker’s Biography\nPing ZHANG\, Academician of the Chinese Academy of Engineering\, IEEE Fellow\, Professor in the  Beijing University of Posts and Telecommunications\, Ph.D. Supervisor\, Director of the State Key Laboratory of Networking and Switching Technology. He is the Editor-in-Chief of the Journal on Communications. He is a member of IMT-2020 (5G) Experts Panel\, a member of the Experts Panel for China’s 6G development\, and has received many awards and honours\, including the Grand Prize for the National Science and Technology Progress Award. He is one of the most well-known key contributors to the development of China-pioneered mobile communication technologies\, which have been widely adopted on a global scale. His research interests include next-generation mobile networks\, semantic communications\, and intellicise communication systems. \nAll are welcome! We are looking forward to seeing you in the lecture! \nSupported By\n \nAll are welcome! We are looking forward to seeing you in the lecture! \nRegistration Link: https://hkuems1.hku.hk/hkuems/ec_hdetail.aspx?guest=Y&ueid=102673 \n**********************(Chinese version)****************************\n \n講者：张平教授，北京邮电大学 \n摘要： \n语法通信以美国科学家香农信息论为标志，为信息度量、压缩、传输等指明了发展方向，它的理论完备、工程可行，构成了完善的信息通信技术。然而，经过了近80年的发展，语法通信已经进入了瓶颈。一是后摩尔时代芯片尺寸与元器件规模的矛盾日益突出，冯·诺依曼结构带来的局限日渐明显，移动通信的技术堆砌式演进受到芯片工艺、器件及计算结构等严重限制；二是从香农信道容量公式可以看出，增加天线、频谱、功率等物理维度，尽管可提升系统容量，但资源消耗巨大，难以可持续发展；三是不同类型机器人等新型通信对象不断涌现，与人类的通信需求和信息接收方式差异巨大。因此，需要颠覆性创新实现新的需求！ \n本报告从基础理论、核心方法、设计思想等层面来阐述这种革新带来的变化。作为一种新的通信范式，语义通信颠覆了传统的通信技术体系，为通信与智能融合开辟了创新技术途径，在基础理论研究、核心技术攻关、工程试验验证等三个层面方面均取得了突破性的成绩。目前正在越来越广泛的被业界认可与同行。最后，本报告从工程试验验证的角度证实语义通信确实是6G的“拐点”技术，证明了AI可以和无线通信融合，高效地克服知识、模型网络传递 “最后一公里”的难题。语义通信的突破带来了传统通信系统设计的变革，它不再是代际演变时采用传统延长线碎片化的创新，而是采用强大的AI与通信系统模块化、低成本、可解释的优化融合，获得了融合系统性能巨大的增益。 \n講者簡介：\n张平，国务院参事，中国工程院院士，北京邮电大学教授、博士生导师、网络与交换技术国家重点实验室主任，《通信学报》主编，IEEE Fellow等。长期致力于移动通信理论研究和技术创新，担任IMT- 2020（5G）专家组成员、IMT-2030（6G）推进组咨询委员会委员，先后获国家科学技术进步奖特等奖等多项奖励，为我国自主技术成为国际主流做出了基础性的贡献。目前研究兴趣聚焦在语义通信和语用达意网络。 \n歡迎大家踴躍參加！我們期待你來參加這次的演講！ \n按此立即登記！ URL:https://ece.hku.hk/events/20250916-1/ LOCATION:Tam Wing Fan Innovation Wing Two\, G/F\, Run Run Shaw Building\, The University of Hong Kong CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/08/20250916-1-Public-1280.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250916T133000 DTEND;TZID=Asia/Hong_Kong:20250916T153000 DTSTAMP:20260510T001708 CREATED:20250829T071751Z LAST-MODIFIED:20250909T083854Z UID:113148-1758029400-1758036600@ece.hku.hk SUMMARY:HKU Centennial Distinguished Chinese Scholars Scheme – Scientific Lecture: Theoretical Foundations and Practical Implementation of Semantic Communications (语义通信的理论基础和试验验证) DESCRIPTION:Registration Link: https://hkuems1.hku.hk/hkuems/ec_hdetail.aspx?guest=Y&ueid=102674 \nKindly note that the lecture will be conducted in Putonghu. \nSpeaker\nProf. Ping ZHANG\, Beijing University of Posts and Telecommunications \nAbstract\nThe deep integration of communication and intelligence is driving a fundamental transformation in next-generation wireless systems. Traditional networks face significant challenges in scalability\, adaptability\, and flexibility\, falling to meet the demands for ubiquitous intelligence and sustainable development. To address these limitations\, semantic wireless networks with their inherent characteristics of intelligence-endogenous and primitive-concise\, have been proposed as a transformative paradigm. Built on native cognition and learning capabilities\, semantic wireless networks evolve communication systems from passive data pipelines into proactive intelligent agents\, enabling widespread digital transformation across industries. This talk will focus on the core principles and practices of semantic wireless networks\, including semantic information theory\, semantic communication\, semantic network architecture\, and field test networks for 6G. Promising application scenarios and future directions will also be discussed. \nSpeaker’s Biography\nPing ZHANG\, Academician of the Chinese Academy of Engineering\, IEEE Fellow\, Professor in the Beijing University of Posts and Telecommunications\, Ph.D. Supervisor\, Director of the State Key Laboratory of Networking and Switching Technology. He is the Editor-in-Chief of the Journal on Communications. He is a member of IMT-2020 (5G) Experts Panel\, a member of the Experts Panel for China’s 6G development\, and has received many awards and honours\, including the Grand Prize for the National Science and Technology Progress Award. He is one of the most well-known key contributors to the development of China-pioneered mobile communication technologies\, which have been widely adopted on a global scale. His research interests include next-generation mobile networks\, semantic communications\, and intellicise communication systems. \nSupported By\n \nAll are welcome! We are looking forward to seeing you in the lecture! \nRegistration Link: https://hkuems1.hku.hk/hkuems/ec_hdetail.aspx?guest=Y&ueid=102674\n**********************(Chinese version)****************************\n \n講者：张平教授，北京邮电大学 \n摘要：\n通信与智能的深度融合正在推动下一代无线系统的根本性变革。传统网络在可扩展性、适应性和灵活性方面面临重大挑战，无法满足无处不在的智能和可持续发展的需求。为了解决这些局限性，语义无线网络具有智能内生性和原生智能的固有特征，被作为一种新的变革范式。语义无线网络基于原生认知和学习能力，将通信系统从被动数据管道发展为主动智能代理，实现跨行业的广泛数字化转型。本次演讲将重点讨论语义无线网络的核心原理和实践，包括语义信息理论、语义通信、语义网络架构和 6G 现场测试网络。还将讨论有前景的应用场景和未来方向。 \n講者簡介：\n张平，国务院参事，中国工程院院士，北京邮电大学教授、博士生导师、网络与交换技术国家重点实验室主任，《通信学报》主编，IEEE Fellow等。长期致力于移动通信理论研究和技术创新，担任IMT- 2020（5G）专家组成员、IMT-2030（6G）推进组咨询委员会委员，先后获国家科学技术进步奖特等奖等多项奖励，为我国自主技术成为国际主流做出了基础性的贡献。目前研究兴趣聚焦在语义通信和语用达意网络。 \n歡迎大家踴躍參加！我們期待你來參加這次的演講！ \n按此立即登記！ URL:https://ece.hku.hk/events/20250916-2/ LOCATION:Tam Wing Fan Innovation Wing Two\, G/F\, Run Run Shaw Building\, The University of Hong Kong CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/08/20250916-1-Scientific-1280.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250918T110000 DTEND;TZID=Asia/Hong_Kong:20250918T120000 DTSTAMP:20260510T001708 CREATED:20250901T075531Z LAST-MODIFIED:20250909T024245Z UID:113154-1758193200-1758196800@ece.hku.hk SUMMARY:Seminar on Hierarchical Modular Organisation in the Brain: Segregation\, Integration and Their Balance Underlying Cognitive Diversity DESCRIPTION:Abstract\nThe brain is a highly nonlinear complex network system supporting diverse cognitive abilities. The locally segregated and globally integrated processing are the two basic foundations of cognition. However\, how the brain organises the effective processing of neural information at both local and global scales\, so as to support diverse cognitive tasks\, is not well understood. A physical hypothesis is that the brain system is in a dynamic critical state at rest and can support the balance of separation and integration in supporting diverse cognitive abilities. However\, there has been no clear evidence on whether the resting brain is in the segregation-integration balance at the whole-brain scale\, and how it is associated with diverse cognitive abilities. We address the above open interdisciplinary question using an eigenmode-based approach to identify hierarchical modules in structural and functional brain networks by combining large-scale models and fMRI data. The structural brain network displays hierarchical modular organisation inherently supporting multilevel segregation and integration modes. We found that the critical state can best recruit such hierarchical modes to maximise the diversity in the functional connectivity. In a large sample of healthy young adults (n=991) from the Human Connectome Project (HCP)\, we demonstrate that resting brain functional networks are on average close to a balanced state. This state allows for a balanced time dwelling at segregated and integrated configurations\, and highly flexible switching between them. Meanwhile\, we demonstrate that network segregation\, integration and their balance in resting brains predict individual differences in diverse cognitive phenotypes. We also show that weak links\, which are largely ignored in network neuroscience\, play a crucial role in supporting the segregation-integration balance and cognitive functions. Our findings provide a systems-level understanding of the brain’s functioning principles in supporting diverse functional demands and cognitive abilities\, and advance modern network neuroscience theories of human cognition\, which may shed light on dysfunctional segregation and integration in neurodegenerative diseases and neuropsychiatric disorders. Examples of application of the framework to stress and ADHD are briefly presented. \nSpeaker\nProf. Changsong ZHOU\nChair Professor of Physics and Complex Systems\,\nDepartment of Physics;\nDirector of Centre for Nonlinear Studies;\nDirector of Institute of Computational and Theoretical Studies;\nDirector of Life Science Imaging Centre (LSIC)\,\nHong Kong Baptist University \nSpeaker’s Biography\nProf. Changsong ZHOU\, Chair Professor of Physics and Complex Systems in the Department of Physics\, Director of Centre for Nonlinear Studies\, Director of the University Central Research Facility Life Science Imaging Centre\, Director of Institute of Computational and Theoretical Studies\, Hong Kong Baptist University (HKBU)\, and RGC Senior Research Fellow 2023. He received the HKBU President’s Award for Outstanding Young Researcher 2011 and the President’s Award for Outstanding Performance in Scholarly Work 2021. His research interests are analysis and modelling of complex connectivity and activity in neural systems using physical science approaches in collaboration with experimental neuroscientists. He has published over 180 research papers in interdisciplinary journals such as Nature Communications\, PNAS\, and Physical Review Letters. \nOrganiser\nDr. Alex Tze Lun LEONG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nSupported By URL:https://ece.hku.hk/events/20250918-1/ LOCATION:Tam Wing Fan Innovation Wing Two\, G/F\, Run Run Shaw Building\, The University of Hong Kong CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/09/1280-2.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250930T103000 DTEND;TZID=Asia/Hong_Kong:20250930T113000 DTSTAMP:20260510T001708 CREATED:20260128T064249Z LAST-MODIFIED:20260128T064249Z UID:114711-1759228200-1759231800@ece.hku.hk SUMMARY:Seminar on AI Contrast Agents – AI to Eliminate Chemical Contrast Agents in Imaging DESCRIPTION:Abstract\nChemical contrast agents have long been integral to clinical diagnostic imaging. However\, growing concerns about their safety\, cost\, and environmental impact have prompted the need for alternative solutions. In this talk\, Dr. Shuo Li will present his pioneering work on AI contrast-enhanced imaging—a transformative approach that leverages cutting-edge machine learning techniques to synthesize contrast-enhanced images without the use of chemical agents. This innovative technology not only reduces patient risk and healthcare costs but also opens new frontiers for precision imaging. Dr. Li will showcase recent breakthroughs from his lab\, highlight clinical applications across cardiology\, oncology\, and neurology\, and discuss the future potential of AI-driven imaging in reshaping medical diagnostics. \nSpeaker\nProf. Shuo Li\nLeonard Case\, Jr. Endowed Professor\,\nCase Western Reserve University \nSpeaker’s Biography\nProf. Li is a global leader in conducting multi-disciplinary research to enable artificial intelligence (AI) in healthcare. He is a Leonard Case\, Jr. endowed professor at Case Western Reserve University (USA). Before that\, he was an associate professor at Western University (Canada) and a scientist at the Lawson Health Research Institute. He was a scientist at GE Healthcare (2006-2015). He is a committee member in multiple highly influential conferences and societies. He is most notable for serving on the prestigious board of directors in the MICCAI society (2015-2024)\, where he is also the general chair for the MICCAI 2022 conference\, which is the most influential AI-in-imaging conference. He has over 300 publications\, acted as the editor for six Springer books\, and serves as an associate editor for several prestigious journals in the field. Throughout his career\, he has received several awards from GE\, various institutes\, and international organisations. He is a Fellow of SPIE\, AAIA\, IET\, AIMBE\, and IAMBE\, and a member of the National Academy of Artificial Intelligence (NAAI). \nOrganiser\nProf. Cheng Chen\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome! URL:https://ece.hku.hk/events/20250930-1/ CATEGORIES:Highlights ATTACH;FMTTYPE=image/png:https://ece.hku.hk/wp-content/uploads/2026/01/dfdfd.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20251025T090000 DTEND;TZID=Asia/Hong_Kong:20251025T180000 DTSTAMP:20260510T001708 CREATED:20251017T090444Z LAST-MODIFIED:20251020T024407Z UID:113635-1761382800-1761415200@ece.hku.hk SUMMARY:HKU Information Day 2025 x EEE Project Demonstrations 香港大學本科入學資訊日 x 電機電子工程專案示範 DESCRIPTION:The Department of Electrical and Electronic Engineering (HKU-EEE) will hold a series of activities on the HKU Information Day on October 25\, 2025 (Saturday).  Join us for admissions talks\, explore the Faculty of Engineering’s main exhibition\, and engage in project demonstrations. Complete two missions at designated booth^ for a chance to win an exclusive gift!  See you there! \n港大電機電子工程系將於2025年10月25日(星期六）的港大本科入學資訊日舉辦一系列的活動。歡迎大家參與本系的招生講座，探索工程學院的主展覽區，並參與專案示範。在指定攤位^完成兩個任務，即可有機會獲得專屬小禮物！到時見！ \nHighlights 亮點: \n\nFaculty of Engineering Main Exhibition 工程學院主展覽區 (HKU-EEE | JS6987)^\n4/F Podium\, Haking Wong Building (Near HKU MTR Exit A2)\n黃克競樓4樓平台 (近香港大學地鐵站A2出口)\nProject Demonstrations 專案示範\nInteractive Booths / 互動展覽區\nG/F Foyer\, Composite Building (Outside Starbucks)\n綜合大樓地下大堂 (星巴克外) \nLaboratory Tour / 實驗室參觀\nLG-303\, LG3/F\, Chow Yei Ching Building\n周亦卿樓LG3樓 LG303室\nUG Admission Talks 本科生入學講座 (BEng | JS6987)\nLecture Theatre A\, G/F\, Chow Yei Ching Building\n周亦卿樓地下演講堂A\n10:30 am – 11:00 am  /  01:15 pm – 01:45 pm  /  04:00 pm – 04:30 pm\n\n \nVisit the Faculty website for the event details  於港大工程學院網頁查看更多活動詳情:\nhttps://engg.hku.hk/News-Events/Details/id/8589 \nClick HERE to view more about the UG programmes offered by HKU-EEE (JS6987).\n按此查看更多關於本系的本科課程（JS6987）。 \n \nAdmissions for HKU Engineering UG students 港大工程本科招生:\nhttps://www.ugadmissions.engg.hku.hk \n \n  URL:https://ece.hku.hk/events/20251025-1/ LOCATION:The University of Hong Kong CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/10/IG-scaled.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20251105T140000 DTEND;TZID=Asia/Hong_Kong:20251105T150000 DTSTAMP:20260510T001708 CREATED:20251030T075345Z LAST-MODIFIED:20251031T044737Z UID:113735-1762351200-1762354800@ece.hku.hk SUMMARY:Seminar on Seeing Beyond Vision: RF-Based Perception for Robust and Intelligent Sensing DESCRIPTION:Abstract\nPerception and understanding of the physical world are fundamental to a wide range of applications\, from autonomous systems to smart healthcare and human-computer interaction. However\, traditional vision-based sensing (e.g.\, cameras and LiDAR) struggles in adverse weather conditions and occlusions. In this talk\, I will discuss how radio frequency (RF) signals provide a powerful alternative by penetrating visual barriers while maintaining high-resolution imaging capabilities. I will present our latest research on RF-based perception systems\, including high-resolution 3D RF imaging and RF-based SLAM for large-scale mapping. Our work leverages advanced signal processing and machine learning to bridge the gap between RF perception and optical sensing. I will conclude with a discussion on the future of RF-based sensing in autonomous vehicles\, smart healthcare\, and cyber-physical systems. \nSpeaker\nProf. Mingmin ZHAO\nAssistant Professor\,\nDepartment of Computer and Information Science\,\nUniversity of Pennsylvania \nSpeaker’s Biography\nMingmin ZHAO is an Assistant Professor in the Department of Computer and Information Science at the University of Pennsylvania\, where he leads the Wireless\, Acoustic\, Vision & Electronics for Sensing (WAVES) Lab. His research focuses on novel sensing modalities that leverage radio frequency (RF) signals\, AI\, and machine learning to enable robust perception in challenging environments. He is a recipient of the ACM SIGMOBILE Doctoral Dissertation Award Runner-up\, the ACM SIGMOBILE Research Highlights\, the CACM Research Highlights\, the Baidu Fellowship\, and the Yunfan Award for Rising Stars in AI. His research on contactless health monitoring has been adopted by the industry and deployed in major hospitals and patients’ homes across the United States. He received his Ph.D. from the Electrical Engineering and Computer Science Department at MIT in 2021\, and his B.S. in Computer Science from Peking University in 2015. \nOrganiser\nProf. Edith C. H. NGAI\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong URL:https://ece.hku.hk/events/20251105-1/ LOCATION:Tam Wing Fan Innovation Wing Two\, G/F\, Run Run Shaw Building\, The University of Hong Kong CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/10/web-banner4.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20251107T103000 DTEND;TZID=Asia/Hong_Kong:20251107T113000 DTSTAMP:20260510T001708 CREATED:20251021T065855Z LAST-MODIFIED:20251021T075021Z UID:113661-1762511400-1762515000@ece.hku.hk SUMMARY:AI-Empowered Mobile Edge Computing Networks DESCRIPTION:Abstract\nThis talk explores the emerging paradigm of AI-empowered mobile edge computing (MEC)\, where edge nodes jointly perform wireless communication\, computation\, and sensing close to users. By colocating learning with connectivity and sharing hardware and spectrum\, MEC cuts latency and energy while enabling advanced\, privacy-aware services at scale. We focus on three pillars and demonstrate how their structure can be leveraged at the edge: (1) machine learning on encrypted data\, showing how ciphertext-compatible training/inference and federated orchestration deliver useful models without exposing raw data; (2) an edge-native metaverse\, where rendering\, state sync\, and perception are partitioned across device-edge-cloud for millisecond responsiveness; and (3) ML for cyberattack detection\, protecting networks from emerging attacks in real-time. \nSpeaker\nProf. Hoang DIHN\nUniversity of Technology Sydney\, Australia \nSpeaker’s Biography\nProf. Hoang DIHN received his Ph.D. degree from the School of Computer Science and Engineering\, Nanyang Technological University\, Singapore\, in 2016. He is currently an associate professor at the University of Technology Sydney (UTS)\, Australia. Over the last ten years\, he has significantly contributed to advanced wireless communications and networking systems. His excellent record evidences this with one patent filed by Apple Inc.\, five books\, eight book chapters\, more than 120 IEEE Q1 journals and 80+ flagship IEEE conference papers in communications and networking. Most of his journal papers have been published in top IEEE journals\, including IEEE JSAC\, IEEE TWC\, IEEE COMST\, and IEEE TMC. Furthermore\, his research papers have had a high impact\, evidenced by more than 20\,000 citations over the last ten years.  Since joining UTS in 2018\, he has received more than AUD 6 million in external funding and several precious awards\, including the Australian Research Council Discovery Early Career Researcher Award for his project “Intelligent Backscatter Communications for Green and Secure IoT Networks\,” IEEE TCSC Award for Excellence in Scalable Computing for Contributions on “Intelligent Mobile Edge Computing Systems” (Early Career Researcher)\, and IEEE TCI Rising Star Award for “Technical Contributions on the Internet.” Alternatively\, he is the lead author of two authored books\, “Ambient Backscatter Communication Networks\,” published by Cambridge University Press in 2020\, and “Deep Reinforcement Learning for Wireless Communications and Networking\,” published by IEEE-Wiley Publisher in 2022. He is currently an Editor of IEEE TMC\, IEEE TWC\, IEEE TCCN\, IEEE TVT\, and IEEE COMST. \nRead more Prof. Dihn’s biography: https://profiles.uts.edu.au/Hoang.Dinh \nOrganiser\nProf. Hongyang DU\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong\n\nAll are welcome! URL:https://ece.hku.hk/events/20251107-1/ 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/2025/10/20251107-1-02.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20251107T160000 DTEND;TZID=Asia/Hong_Kong:20251107T170000 DTSTAMP:20260510T001708 CREATED:20251103T012306Z LAST-MODIFIED:20251103T012306Z UID:113776-1762531200-1762534800@ece.hku.hk SUMMARY:(Sub-)Terahertz Wireless Communications in 6G and Beyond DESCRIPTION:Abstract\nFor decades\, the (sub-)terahertz (THz) frequency band (often defined as 300 GHz to 3 THz or broader\, 100 GHz – 10 THz) had been primarily explored in the context of radar\, imaging\, and spectroscopy\, where multi-gigahertz (GHz) and even THz-wide channels and the properties of terahertz photons offered attractive target accuracy\, resolution\, and classification capabilities. Meanwhile\, the exploitation of the terahertz band for wireless communication had originally been limited due to several reasons\, including (i) no immediate need for such high data rates available via terahertz bands and (ii) challenges in designing sufficiently high-power terahertz systems at reasonable cost and efficiency\, leading to what was often referred to as “the terahertz gap”. In theory\, the use of multi-GHz wide bands available in the THz spectrum also offers unprecedented opportunities for wireless links: up to Terabit-per-second data rate\, sub-millisecond latency\, and extreme secrecy of transmissions\, among others. Over the recent decade\, advances on many fronts have drastically changed the terahertz landscape. Some research contributions even claim that THz communications are an “essential enabler of 6G-grade connectivity”. However\, today\, there are many misconceptions related to THz communications and their possible role in 6G and beyond-6G networks. This short talk aims to clarify those misconceptions\, outline the real pressing challenges\, and\, finally\, discuss some latest R&D activities and results in the area. \nSpeaker\nProf. Vitaly PETROV\nKTH Royal Institute of Technology\, Stockholm\, Sweden \nSpeaker’s Biography\nVitaly PETROV is an Assistant Professor and Head of TERANET@KTH Research Lab\, Division of Communication Systems\, KTH Royal Institute of Technology\, Sweden. Before joining KTH in 2024\, he was a Principal Research Scientist at Northeastern University\, Boston\, MA\, USA (2022-2024) and a Senior Standardisation Specialist and a 3GPP RAN1 delegate with Nokia Bell Labs and later Nokia Standards (2020-2022). Vitaly received his PhD degree in communications engineering from Tampere University\, Finland\, in 2020. His research interests include mobile near-field terahertz band communications and networking. \nOrganiser\nProf. Kaibin HUANG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome! URL:https://ece.hku.hk/events/20251107-2/ 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/2025/11/1280.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20251110T163000 DTEND;TZID=Asia/Hong_Kong:20251110T173000 DTSTAMP:20260510T001708 CREATED:20251106T094008Z LAST-MODIFIED:20251106T100516Z UID:113831-1762792200-1762795800@ece.hku.hk SUMMARY:3D Intelligent Metasurfaces and Their Applications DESCRIPTION:Abstract\nIn this talk\, we will introduce two innovative types of 3D intelligent metasurfaces: Stacked Intelligent Metasurfaces (SIM) and Flexible Intelligent Metasurfaces (FIM). We will explore their exciting applications in wireless communication and sensing systems. Specifically\, SIM is a groundbreaking computing architecture that enables joint signal processing and communication in the electromagnetic (EM) domain. A SIM is fabricated by stacking an array of programmable metasurface layers\, where each layer consists of many low-cost passive meta-atoms that can individually manipulate EM waves. By appropriately configuring the passive meta-atoms\, a SIM can automatically accomplish advanced computation tasks as the EM wave propagates through it while reducing both energy consumption and processing delay. By contrast\, an FIM takes a different approach to leverage the 3D physical space. An FIM is composed of an array of low-cost radiating elements\, each of which can independently radiate electromagnetic signals while flexibly adjusting its position along the direction perpendicular to the surface. Hence\, unlike conventional rigid 2D antenna arrays\, the FIM surface shape may be dynamically reconfigured to improve the channel quality by beneficial 3D morphing. \nSpeaker\nProf. Chau YUEN\nAssociate Professor\,\nNanyang Technological University \nSpeaker’s Biography\nChau YUEN received the B.Eng. and Ph.D. degrees from Nanyang Technological University\, Singapore\, in 2000 and 2004\, respectively. He was a Post-Doctoral Fellow with Lucent Technologies Bell Labs\, Murray Hill\, in 2005. From 2006 to 2010\, he was with the Institute for Infocomm Research\, Singapore. Since 2023\, he has been with the School of Electrical and Electronic Engineering\, Nanyang Technological University. Dr. Yuen received IEEE Communications Society Leonard G. Abraham Prize (2024)\, IEEE Communications Society Best Tutorial Paper Award (2024)\, IEEE Communications Society Fred W. Ellersick Prize (2023)\, IEEE Marconi Prize Paper Award in Wireless Communications (2021)\, IEEE APB Outstanding Paper Award (2023)\, and EURASIP Best Paper Award for JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING (2021).  He is an IEEE Fellow and also a Highly Cited Researcher by Clarivate Web of Science. \nOrganiser\nProf. Kaibin HUANG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong\n\nAll are welcome! URL:https://ece.hku.hk/events/20251110-1/ 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/2025/11/1280-1.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20251117T110000 DTEND;TZID=Asia/Hong_Kong:20251117T120000 DTSTAMP:20260510T001708 CREATED:20251106T070600Z LAST-MODIFIED:20251110T064624Z UID:113828-1763377200-1763380800@ece.hku.hk SUMMARY:💡 Informational Webinar on the MSc(Eng)ICES (Integrated Circuits and Electronic Systems) Admissions for 2026/27 ✨ DESCRIPTION:MSc(Eng)ICES is a new programme jointly offered by the Department of Electrical & Electronic Engineering (EEE)\, Faculty of Engineering\, The University of Hong Kong (HKU) and the Center for Advanced Semiconductors and Integrated Circuits. Prof. Yuhao ZHANG and Prof. Han WANG\, the Programme Directors of the Master of Science in Integrated Circuits and Electronic Systems (MSc(Eng)ICES) programme and the committee members will give an online admissions talk via Zoom. \nPlease find the details as follows: \n📅 Date: November 17\, 2025 (Monday)\n🕒 Time: 11:00 am – 12:00 pm (HKT)\n🔗 Zoom Link: https://hku.zoom.us/j/94597307927\n📍 Meeting ID: 945 9730 7927 \nIn the talk\, details about the Integrated Circuits and Electronic Systems discipline\, career prospects\, programme structure\, and admission requirements will be covered. At the end of the talk\, an interesting interactive Q&A session is waiting for you. All students\, parents and teachers are welcome to attend the talk and be familiar with the latest admissions information. We are looking forward to seeing you! \nThe MSc(Eng)ICES application for 2026/27 is now open. To visit the admissions website\, please click HERE. 📝 \nRelated news: https://ece.hku.hk/20251010-1 URL:https://ece.hku.hk/events/20251117-1/ LOCATION:Online via Zoom CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/11/Untitled-1.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20251120T160000 DTEND;TZID=Asia/Hong_Kong:20251120T170000 DTSTAMP:20260510T001708 CREATED:20251104T030128Z LAST-MODIFIED:20251104T030338Z UID:113822-1763654400-1763658000@ece.hku.hk SUMMARY:Exploring Careers in Industry: Quantitative Research Talk DESCRIPTION:About the Talk\nThe talk is co-organised by Susquehanna and Prof. Kenneth Kin-Yip WONG from the Department of Electrical and Electronic Engineering at The University of Hong Kong. This is a unique opportunity to explore careers in quant trading\, hear firsthand from an experienced researcher\, and connect with industry professionals. \nThe speaker\, Dr. Davor OBRADOVIC\, holds a PhD in Computer Science from the University of Pennsylvania and has been a Quantitative Researcher at Susquehanna for 24 years. He’ll share insights into the quant trading landscape\, how academic research translates into solving complex trading problems\, and what life is like at Susquehanna. \nWhy Attend?\n\nDiscover how your academic background can thrive in industry\nGain insider knowledge about the quant trading field\nNetwork with Susquehanna professionals over refreshments\nReceive exclusive Susquehanna-branded merchandise\n\nRefreshments will be provided during the talk. 😊\n \nTarget Audience\nEEE RPg Students and Postdocs are welcome! \nRegister Now\nhttps://ece.hku.hk/20251120-s \nWe look forward to seeing you at the talk! URL:https://ece.hku.hk/events/20251120-1/ LOCATION:Room LE-9\, LG2/F\, Library Extension Building (LE)\, The University of Hong Kong CATEGORIES:Career Talks,Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/11/1920.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20251121T110000 DTEND;TZID=Asia/Hong_Kong:20251121T120000 DTSTAMP:20260510T001708 CREATED:20251113T061708Z LAST-MODIFIED:20251113T061708Z UID:113884-1763722800-1763726400@ece.hku.hk SUMMARY:Seminar on Probing Arousal Modulation of Brain Networks Using Multimodal Functional MRI in Awake Rodents and Non-human Primates DESCRIPTION:Abstract\nArousal fluctuation is known to contribute to fMRI based functional dynamics\, but its detailed mechanism is largely unclear. Combining invasive neural recording (electrophysiological recording and fiber photometry) and manipulation (optogenetics and chemogenetics) techniques with awake\, unanesthetized animal fMRI provides unique opportunities to unravel the arousal contribution. Highly optimized unanesthetized mouse and marmoset fMRI setups allowed a wide range of arousal states from high alertness to NREM and REM sleep\, which was identified through simultaneous electrophysiological recording. Dynamic functional connectivity analysis revealed an inverted U-shape modulation of global functional connectivity strength and functional gradient from low to high arousal level. Further combined with simultaneous fiber photometry\, our multimodal fMRI revealed direct relationship between Locus Coeruleus Norepinephrine (LC-NE) system and such modulation. Direct neuronal manipulation using optogenetics/chemogenetics simultaneously with awake mouse fMRI confirmed the causal contribution of LC-NE system to inverted u-shape modulation. In conclusion\, multimodal fMRI in awake rodent and non-human primate revealed arousal modulated inverted U-shaped functional connectivity dynamics\, which can be driven by LC-NE activity. \nSpeaker\nDr. Zhifeng LIANG\nSenior Investigator\,\nDirector of the Brain Imaging Center\,\nInstitute of Neuroscience\,\nChinese Academy of Sciences\, Shanghai \nSpeaker’s Biography\nZhifeng LIANG obtained his Bachelor of Science in Life Sciences from Fudan University and PhD in Neuroscience from the University of Massachusetts Medical School. He conducted his postdoc training at the Department of Biomedical Engineering\, Pennsylvania State University\, before joining the Institute of Neuroscience (ION)\, Chinese Academy of Sciences as an Investigator and director of 9.4T animal MRI facility. He is now Senior Investigator and Director of the Brain Imaging Center at the Institute of Neuroscience\, with a research focus on multimodal fMRI techniques and applications in neuroscience. \nOrganiser\nDr. Alex Tze Lun LEONG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAcknowledgement\nTam Wing Fan Innovation Wing Two\n\nAll are welcome! URL:https://ece.hku.hk/events/20251121-1/ LOCATION:Tam Wing Fan Innovation Wing Two\, G/F\, Run Run Shaw Building\, The University of Hong Kong CATEGORIES:Highlights,Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/11/1280-2.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20251202T140000 DTEND;TZID=Asia/Hong_Kong:20251202T150000 DTSTAMP:20260510T001708 CREATED:20251113T062320Z LAST-MODIFIED:20251126T063144Z UID:113888-1764684000-1764687600@ece.hku.hk SUMMARY:Seminar on Bi-Static Sensing for Next Generation Perceptive Communication Networks: Technologies and Applications DESCRIPTION:The event time has been revised to start at 2:00 pm. \nAbstract\nIntegrated Sensing and Communications (ISAC) represents a paradigm shift from conventional communication-only networks toward systems that natively integrate radar-like sensing capabilities. It has become a foundational technology for next-generation wireless systems\, including Wi-Fi and 6G networks. \nBi-static sensing\, where a sensing receiver exploits signals transmitted by another node\, naturally aligns with the topology of communication networks. It circumvents the stringent full-duplex requirements of mono-static sensing and offers enhanced spatial sensing diversity. However\, clock (Local oscillating signal) asynchronism\, which inherently exists among spatially separated communication nodes\, poses a central and challenging problem. It can cause ranging ambiguities and disrupt coherent processing of discontinuous measurements\, such as those required for Doppler frequency estimation. If effectively resolved\, sensing could be seamlessly realised within existing communication infrastructures\, requiring minimal hardware or architectural modifications. \nThis talk explores advanced techniques for tackling clock asynchronism in bi-static sensing\, with a focus on efficient single-receiver-based solutions. The problem will first be introduced in the context of 6G perceptive mobile networks\, followed by a comprehensive overview of recent methods applicable to both multi-antenna and single-antenna configurations. I will then present our latest sensing applications developed using these techniques\, including moving-object tracking\, respiration and heartbeat monitoring\, behavior recognition\, and environmental sensing such as rainfall and water-level detection. The talk concludes by outlining key open challenges and future research directions in this rapidly evolving field. \nSpeaker\nProf. Andrew ZHANG\nUniversity of Technology Sydney \nSpeaker’s Biography\nProf. J. Andrew ZHANG (M’04-SM’11) is a Professor in the School of Electrical and Data Engineering\, University of Technology Sydney\, Australia. His research interests are in the area of signal processing for wireless communications and sensing. He has published more than 300 papers in leading Journals and conference proceedings\, and has won 7 best paper awards. He is a recipient of CSIRO Chairman’s Medal and the Australian Engineering Innovation Award for exceptional research achievements in multi-gigabit wireless communications. He is one of the pioneer researchers in ISAC. He initiated the concept of perceptive mobile network in 2017. Since then\, his team has published more than 70 top-tier journal papers on ISAC\, including several highly cited and review articles. In this field\, he has led or participated in multiple research projects with a total value of over AUD 8 million\, established a Joint Laboratory on Network Sensing with a mobile network operator\, developed multiple real-time ISAC demonstration systems\, and is currently advancing their commercialisation. Prof. Zhang co-organised a number of ISAC workshops at leading conferences and special issues in leading IEEE journals. He has also delivered multiple ISAC tutorials and numerous keynotes and invited talks. For details\, please refer to Prof. Zhang’s profile page: https://sites.google.com/view/andrewzhang \nOrganiser\nProf. Kaibin HUANG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong\n\nAll are welcome! URL:https://ece.hku.hk/events/20251202-1/ 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/2025/11/1280-7.jpg END:VEVENT END:VCALENDAR