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-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:20251126T140000 DTEND;TZID=Asia/Hong_Kong:20251126T150000 DTSTAMP:20260510T224204 CREATED:20251119T043408Z LAST-MODIFIED:20251119T043408Z UID:113999-1764165600-1764169200@ece.hku.hk SUMMARY:RPG Seminar – Hardware-Adaptive and Superlinear-Capacity Memristor-based Associative Memory DESCRIPTION:Zoom Link: https://hku.zoom.us/j/99913066038?pwd=qqqBn1ojbFqbJJ4Koun6hucopMT2rJ.1 \nAbstract\nBrain-inspired computing aims to mimic cognitive functions like associative memory\, the ability to recall complete patterns from partial cues. Memristor technology offers promising hardware for such neuromorphic systems due to its potential for efficient in-memory analog computing. Hopfield Neural Networks (HNNs) are a classic model for associative memory\, but implementations on conventional hardware suffer from efficiency bottlenecks\, while prior memristor-based HNNs faced challenges with vulnerability to hardware defects due to offline training\, limited storage capacity\, and difficulty processing analog patterns. Here we introduce and experimentally demonstrate on integrated memristor hardware a new hardware-adaptive learning algorithm for associative memories that significantly improves defect tolerance and capacity\, and naturally extends to scalable multilayer architectures capable of handling both binary and continuous patterns. Our approach achieves 3x effective capacity under 50% device faults compared to state-of-the-art methods. Furthermore\, its extension to multilayer architectures enables superlinear capacity scaling (∝  for binary patterns) and effective recalling of continuous patterns (∝  scaling)\, as compared to linear capacity scaling for previous HNNs. It also provides flexibility to adjust capacity by tuning hidden neurons for the same-sized patterns. By leveraging the massive parallelism of the hardware enabled by synchronous updates\, it reduces energy by 8.8× and latency by 99.7% for 64-dimensional patterns over asynchronous schemes\, with greater improvements at scale. This promises the development of more reliable memristor-based associative memory systems and enables new applications research due to the significantly improved capacity\, efficiency\, and flexibility. \nSpeaker\nMr. Chengping He\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nChengping He received his B.Eng. and M.S. degrees from the Department of Physics at Nanjing University\, China\, in 2019 and 2022\, respectively. He is currently pursuing a Ph.D. in the Department of Electrical and Electronic Engineering under the supervision of Professor Can Li. His research focuses on in-memory computing\, analog computing\, associative memory\, and software-hardware co-design. \nOrganiser\nProf. Can Li\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251126/ LOCATION:Online via Zoom CATEGORIES: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:20251126T140000 DTEND;TZID=Asia/Hong_Kong:20251126T150000 DTSTAMP:20260510T224204 CREATED:20251117T074555Z LAST-MODIFIED:20251117T074555Z UID:113912-1764165600-1764169200@ece.hku.hk SUMMARY:RPG Seminar – Dynamic Motion Modeling and Planning of Fabric Piece DESCRIPTION:Zoom Link: https://hku.zoom.us/j/9706928305?omn=95929409545 \nAbstract\nUnlike rigid objects\, fabric pieces are difficult for robots to plan motion because they are deformable objects with infinite degrees of freedom\, and their states evolve during robot motion. Instead of using a detailed model\, we propose using an oriented bounding box to approximate the state of the fabric piece. The fabric piece motion is approximated by a Transformer-based neural network. A simple yet effective robot trajectory is designed based on the predicted future motion of the fabric piece. Experimental results on an industrial robot system with a fabric piece demonstrate that the fabric piece can avoid collisions with different obstacles and types of fabric. We then extend this approach to garment dynamic motion planning\, incorporating more complicated oriented bounding box modeling and trajectory design methods. \nSpeaker\nMr. Letian Li\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nLetian Li received the B. Eng. degree in detection\, guidance\, and control technology and the M. Eng. degree in instrumentation science and technology from the School of Instrumentation and Optoelectronic Engineering\, Beihang University\, Beijing\, China\, in 2019 and 2022\, respectively. He is currently pursuing the Ph.D. degree with JC STEM Lab of Robotics for Soft Materials\, Department of Electrical and Electronic Engineering\, Faculty of Engineering\, The University of Hong Kong\, Hong Kong SAR\, China. He is engaged in collaborative research with the Centre for Transformative Garment Production\, Hong Kong SAR\, China. His research interests include motion planning and learning. \nOrganiser\nProf. Kazuhiro Kosuge\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251126-2/ LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong CATEGORIES: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:20251125T160000 DTEND;TZID=Asia/Hong_Kong:20251125T170000 DTSTAMP:20260510T224204 CREATED:20251118T035502Z LAST-MODIFIED:20251118T035502Z UID:113919-1764086400-1764090000@ece.hku.hk SUMMARY:RPG Seminar – Automated Straight-line Sewing of Stretchable Fabrics with Different Lengths DESCRIPTION:Zoom Link: https://hku.zoom.us/j/7425733217?omn=96993354197 \nAbstract\nDifferent Length Alignment Sewing (DLAS)\, which involves stretching the shorter fabric to match the longer one and sewing them together in a straight line\, is a challenging task that needs to satisfy several requirements when automating the sewing process. To address the challenges\, we propose a novel robotic sewing system\, Different Length Robotic Sewing System (DLRoSS)\, which consists of a roller type end-effector\, attached to a 6-DoF manipulator. The end-effector composed of active shorter and longer fabric rollers\, and a passive press-roller attached to the shorter-fabric roller. Assuming that one end of the two fabric layers are initially positioned under the sewing machine’s presser foot\, the system automates DLAS by operating in four distinct phases. (P1) Fabric wrapping: Individual fabric layers are picked\, held\, and wrapped from the other end onto the feed rollers. (P2) Sewing: During the sewing\, the shorter fabric is stretched and aligned with the longer fabric in real- time using roller velocity control based on the sewing speed and apriori known length ratio. (P3) Sewing completion: In the final sewing round on the fabric rollers\, the press roller is engaged to prevent the stretched fabric from slipping off due to internal tension. (P4) Sewing fabric release: At the end of sewing\, the fabric edge moves past the press roller\, and the fabric releases from the rollers. Experimental results demonstrate that DLRoSS achieves consistent\, high-quality sewing of stretchable fabrics of different materials and lengths. \n \nSpeaker\nMr. Bingchen Jin\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nBingchen Jin received his B.Sc. degree in Mechanics and Electronics Engineering from Jiangsu University\, China\, in 2015\, and his M.Sc. degree in Mechanical Engineering from Harbin Institute of Technology (Shenzhen)\, in 2018. From 2019 to 2021\, he was a research assistant in the Chinese University of Hong Kong (Shenzhen). He is currently towards his Ph.D. degree at the Department of Electrical and Electronic Engineering\, The University of Hong Kong\, Hong Kong SAR. He is involved in the Centre for Transformative Garment Production\, Hong Kong SAR. His research focuses on robotics manipulation\, and artificial intelligence. \nOrganiser\nProf. Kazuhiro Kosuge\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251125-3/ LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong CATEGORIES: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:20251125T150000 DTEND;TZID=Asia/Hong_Kong:20251125T160000 DTSTAMP:20260510T224204 CREATED:20251119T064431Z LAST-MODIFIED:20251119T064939Z UID:114022-1764082800-1764086400@ece.hku.hk SUMMARY:RPG Seminar – Diffusion Model Acceleration with RRAM-based In-memory Neural Differential Equation Solver DESCRIPTION:Zoom Link: https://hku.zoom.us/j/93740801215 \nAbstract \nDiffusion models generate high-quality images and videos\, closely mirroring the imagination of human brain. Specifically\, score-based diffusion models generate by solving neural differential equations. However\, their digital computer implementations are discrete in time and inherently digital\, with energy efficiency constrained by the von Neumann architecture. Herein\, we firstly demonstrate a chip-level solution that embodies the implementation of time-continuous and analog conditional score-based diffusion using a Resistive Random Access Memory (RRAM) in-memory neural differential equation solver. Notably\, the score-based diffusion process is intrinsically robust to analog computing noise. We validate our solution on a conditional diffusion task. Our in-memory neural differential equation solver opens a brand-new hardware solution for edge generative AI. \nSpeaker\nMr. Jichang Yang\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nJichang Yang received both his B.Sc. and M.Sc. from the School of Electrical and Electronic Engineering at Huazhong University of Science and Technology\, Wuhan\, China\, in 2019 and 2022\, respectively. He is currently pursuing the Ph.D. degree with the Department of Electrical and Electronic Engineering under the supervision of Prof. Han Wang. His research interests mainly include in-memory computing\, diffusion models\, and software-hardware co-design. \nOrganiser\nProf. Han Wang\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251125-4/ LOCATION:Online via Zoom CATEGORIES: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:20251125T150000 DTEND;TZID=Asia/Hong_Kong:20251125T160000 DTSTAMP:20260510T224204 CREATED:20251118T034820Z LAST-MODIFIED:20251118T035127Z UID:113916-1764082800-1764086400@ece.hku.hk SUMMARY:RPG Seminar – Seam-Informed Garment Handling Using Bimanual Manipulator DESCRIPTION:Zoom Link: https://hku.zoom.us/j/7425733217?omn=96993354197 \nAbstract\nSeams are information-rich components of garments. The presence and combination of different types of seam help to estimate the state of a garment. We introduce a novel Seam-Informed Strategy (SIS) for garment state estimation and planning for garment handling.  In this talk\, we will consider a problem to flatten a T-shirt which is randomly placed on a flat surface and demonstrate how SIS effectively estimate the garment state to facilitate grasp and unfold action. \nSeams are extracted from visual information. The Seam Feature Extraction Method is proposed to formulate seam extraction as an oriented object detection problem. The extracted seams provide an implicit representation of the garment’s structure and are used as grasping point candidates for bimanual flinging to unfold the garment. The Decision Matrix Iteration Method is proposed to select a pair of grasping points from the grasping point candidates. The decision matrix is initialized based on human demonstrations\, then updated using the robot’s execution results to improve its grasping and unfolding policy. Experimental results demonstrate the effectiveness and generalization ability of the proposed strategy. \nSpeaker\nMr. Xuzhao Huang\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nXuzhao Huang received the B.Eng. degree in Mechanical Design\, Manufacturing\, and Automation from Xiamen University\, China\, in 2018\, and the M.Eng. degree in Mechatronics Engineering from the Harbin Institute of Technology\, Shenzhen\, in 2021. He is currently pursuing the Ph.D. degree in Engineering with The University of Hong Kong. His research interests include visual perception and robotic manipulation of deformable objects. \nOrganiser\nProf. Kazuhiro Kosuge\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251125-2/ LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong CATEGORIES: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:20251125T140000 DTEND;TZID=Asia/Hong_Kong:20251125T150000 DTSTAMP:20260510T224204 CREATED:20251117T063039Z LAST-MODIFIED:20251117T063039Z UID:113905-1764079200-1764082800@ece.hku.hk SUMMARY:RPG Seminar – Robot Learning and Control for Fabric Manipulation and Fixture-Free Automated Sewing DESCRIPTION:Zoom Link: https://hku.zoom.us/j/7425733217?omn=96993354197 \nAbstract\nAutomating garment production requires production‑grade precision for each production process across diverse fabrics\, which remains challenging for conventional model-based methods. While model-based control scheme is effective for automating rigid-body handling processes\, it struggles with fabrics’ effectively infinite degrees of freedom\, nonlinear dynamics\, and frequent self-occlusions from wrinkles and folds. End‑to‑end deep learning offers rich representational power to capture fabric states and dynamics for policy learning\, yet existing methods lack the precision\, stability\, and safety guarantees demanded by industrial deployment. \nTo address this challenge\, we present a new robot learning and control paradigm for fabric manipulation in which learning expands the boundary of achievable tasks\, while control guarantees system stability and performance. The paradigm comprises: (i) multi-level perception\, (ii) feedback-structured policy learning\, and (iii) convergence-and-stability assurance. \nWe instantiate this paradigm in fixture-free sewing with a dual-arm manipulator and an ordinary industrial sewing machine. \n\nThe multi-level perception comprises global fabric state estimation using a mesh-based representation with a Graph Attention Network (GAT) and local\, real-time edge detection using High-speed Fabric Edge Detection System (Hi-FEDS)\, enabling global pose tracking\, wrinkle-aware state representation\, and precise seam estimation for real-time sewing.\nThe feedback‑structured policy learning—implemented via Imitation Learning (IL) with the Mesh Action Chunking Transformer (MACT)—operates in a closed‑loop\, error‑driven fashion to drive random wrinkled fabrics toward wrinkle‑free target states.\nOnce the fabrics reach control‑ready initial states\, a model‑based nonlinear controller—using nonholonomic sewing dynamics and time scaling—guarantees exponential convergence and sub‑millimeter steady‑state sewing error. Dual‑arm impedance control regulates internal wrenches applied to the fabric and the external wrenches of the system\, ensuring stability when interacting with passive environments.\n\nSpeaker\nMr. Kai Tang\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nKai Tang received his B.Sc. in Process Equipment and Control Engineering from South China University of Technology in 2020\, and M.Sc. (Distinction) in Control and Optimisation from Imperial College London in 2021. He is currently pursuing Ph.D. in robotics at JC STEM Lab of Robotics for Soft Materials\, the Department of Electrical and Electronic Engineering\, The University of Hong Kong. He is involved in the Centre for Transformative Garment Production\, Hong Kong SAR. His research focuses on robotic fabric manipulation and fixture-free automated sewing using control and deep learning. \nOrganiser\nProf. Kazuhiro Kosuge\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251125/ LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong CATEGORIES: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:20251125T080000 DTEND;TZID=Asia/Hong_Kong:20251125T090000 DTSTAMP:20260510T224204 CREATED:20251120T081820Z LAST-MODIFIED:20251120T081820Z UID:114045-1764057600-1764061200@ece.hku.hk SUMMARY:RPG Seminar – An Acoustic-responsive Hydrogel Electrode for Wearable Deep Brain Stimulation DESCRIPTION:Zoom Link: https://hku.zoom.us/j/94612024859?pwd=Sqldxnoy6vEOP3HqfBBLs1oMxAQvFx.1 \nAbstract\nDeep brain stimulation (DBS) is a powerful therapy for neurological disorders\, yet conventional systems rely on finite-lifetime batteries and rigid implants that necessitate repeated surgeries and pose long-term risks. This seminar presents EchoGel\, a brain-compatible\, acoustic-responsive\, and conductive hydrogel electrode platform designed to enable fully wearable\, battery-free DBS. Once implanted in the brain\, EchoGel harvests external acoustic waves to enable wireless energy transfer and eliminate tethered connections. Its flexible\, needle-shaped hydrogel electrodes then provide stable and long-lasting stimulation. When integrated with a miniaturized wearable acoustic generator\, the system delivers deeper and more durable neuromodulation in freely behaving animals. Together\, these advances establish a path toward safer\, minimally invasive\, and long-lasting DBS technologies. \nSpeaker\nMs. Yilin Yang\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nYilin Yang received her B.Eng. and M.Eng\, both in Biomedical Engineering from Sun Yat-sen University. She is currently a Ph.D. student in the WISE Research Group working on brain-machine interfacing with soft and implantable bioelectronic systems. She is interested in the design\, fabrication\, and characterization of wearable neuromodulation and recording system based on novel soft materials. \nOrganiser\nProf. Shiming Zhang\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251125-5/ LOCATION:Online via Zoom CATEGORIES: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:20251124T150000 DTEND;TZID=Asia/Hong_Kong:20251124T160000 DTSTAMP:20260510T224204 CREATED:20251118T042520Z LAST-MODIFIED:20251118T042520Z UID:113922-1763996400-1764000000@ece.hku.hk SUMMARY:RPG Seminar – Event-augmented 3D Geometry Estimation for Extreme Conditions DESCRIPTION:Zoom Link: https://hku.zoom.us/meetings/92032873265/invitations?signature=ZlnhYyZi056expgN41HYZdcENW6INTs0MyPEhyhl7r8 \nAbstract\nRobust 3D geometry estimation from videos is essential for autonomous navigation\, SLAM\, and 3D reconstruction. While recent pointmap-based methods such as DUSt3R enable accurate pose-free reconstruction\, RGB-only approaches remain fragile under dynamic scenes and extreme illumination. We introduce a geometry estimation framework that augments pointmap reconstruction with asynchronous event data. It features: (1) a retinex-inspired enhancement module and a lightweight event adapter with SNR-aware fusion for adaptive RGB–event integration; and (2) an event-based photometric consistency loss that enforces spatiotemporal coherence during global optimization. Our method delivers robust geometry estimation in dynamic\, low-light environments without night-time retraining\, achieving substantial gains over state-of-the-art RGB-only baselines on monocular depth\, video depth\, and pose tracking.\n \nSpeaker\nMr. Yifei YU\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nYU Yifei received B.E degree from School of Information Science and Technology\, Fudan University\, Shanghai\, China\, in 2022. He is currently pursuing the Ph.D. degree with the Department of Electrical and Electronic Engineering under the supervision of Prof. Xiaojuan Qi. His research interests mainly include in-memory computing\, 3D vision\, neuromorphic computing\, and software-hardware co-design. \nOrganiser\nProf. Xiaojuan Qi\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251124/ LOCATION:Online via Zoom CATEGORIES: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:20251121T143000 DTEND;TZID=Asia/Hong_Kong:20251121T150000 DTSTAMP:20260510T224204 CREATED:20251119T032920Z LAST-MODIFIED:20251119T032920Z UID:113987-1763735400-1763737200@ece.hku.hk SUMMARY:RPG Seminar – Handling collaborative eavesdroppers in secure cell-free system DESCRIPTION:Zoom Link: https://hku.zoom.us/meetings/93247207941/invitations?signature=9mw43b9u1DETwxS1FU3ze_f2GpaMXc_Qr8OHnU4L4c8 \nAbstract\nIn wireless communication system\, physical layer security is an important issue to ensure the data transmission of the communication users. In previous physical layer security problem\, eavesdroppers are considered wiretapping the target signal independently. However\, with the development of intelligent devices\, eavesdroppers can wiretap the signal collaborately. Combined with the covert and passive nature of eavesdroppers\, mitigating the adverse effect of the collaborative eavesdroppers becomes ultimately significant. \nIn this talk\, we try to maximize the secrecy rate of the communication users while restricting the outage probability by eavesdroppers within a limited threshold. In particular\, we provide an asymptotically equivalent transformation of the outage probability under passive and collaborative eavesdroppers. Furthermore\, a zeroth-order algorithm is proposed to handle the resultant optimization problem. \nSpeaker\nMr. Hancheng Zhu\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nHancheng Zhu received the B.Eng. degree from the Faculty of Computer Science and Technology\, Nanjing Tech University\, Nanjing\, China\, and the M.Eng. degree from the Faculty of Information Science and Engineering\, Southeast University\, Nanjing\, China\, in 2015 and 2018\, respectively. He is currently working toward the Ph.D. degree with the Department of Electrical and Electronic Engineering\, The University of Hong Kong\, Hong Kong. His research interests include first-order optimization\, and wireless communication. \nOrganiser\nProf. Yik-Chung Wu\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251121/ LOCATION:Online via Zoom CATEGORIES: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:20251121T110000 DTEND;TZID=Asia/Hong_Kong:20251121T120000 DTSTAMP:20260510T224204 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:20251120T160000 DTEND;TZID=Asia/Hong_Kong:20251120T170000 DTSTAMP:20260510T224204 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:20251120T150000 DTEND;TZID=Asia/Hong_Kong:20251120T160000 DTSTAMP:20260510T224204 CREATED:20251113T070933Z LAST-MODIFIED:20251113T070933Z UID:113894-1763650800-1763654400@ece.hku.hk SUMMARY:RPG Seminar – Fast and efficient genomic analysis with memristor-based in-memory computing hardware DESCRIPTION:Zoom Link: https://hku.zoom.us/j/99194942035?pwd=W2Dch8eGCZCClFk8j97JlRvpcTrpMP.1 \nAbstract\nAdvances in third-generation sequencing (TGS) have unlocked the potential for portable\, real-time genomic analysis\, but data processing remains a critical bottleneck hindering practical on-site applications. The massive\, error-prone data streams generated by these sequencers overwhelm traditional von Neumann architectures\, which are limited by costly data movement. This presentation introduces two novel in-memory computing (IMC) hardware-software codesigns developed to accelerate genomic analysis directly in memory\, specifically targeting the challenges of high error rates and raw signal data. \nThe first work\, ShiftCAM\, addresses the high insertion and deletion (indel) error rates in basecalled reads\, a key challenge for existing CAM-based accelerators. ShiftCAM is a novel time-domain Content Addressable Memory (CAM) that efficiently calculates the Shifted Hamming Distance to better approximate the computationally expensive edit distance. This approach\, combined with a hardware-specific “Modification to Accidental Match” strategy\, significantly reduces false positives. Simulations demonstrate that ShiftCAM achieves a 2.1× higher F1 score in contamination analysis and offers a 29.5× speedup and 9.4× higher energy efficiency over state-of-the-art in-memory classifiers. \nThe second work presents a memristor-based codesign that bypasses basecalling entirely to process raw\, analog sequencer signals directly in analog memory. This system merges the traditionally separate steps of basecalling and read mapping. By exploiting intrinsic memristor device noise for locality-sensitive hashing and implementing parallel approximate search\, our fully integrated chip experimentally demonstrates high-accuracy (97.15% F1 score) infectious disease detection from raw signals. This direct-processing approach yields a 51× speed-up and 477× energy saving over a conventional ASIC. \nCollectively\, these two works demonstrate that specialized in-memory computing architectures provide a powerful and viable solution for integration with portable sequencers. By tackling bottlenecks from indel-rich reads (ShiftCAM) to raw analog signals (memristor-codesign)\, these approaches pave the way for true real-time\, on-site genomic analysis in fields like personalized medicine and metagenomics. \nSpeaker\nMr. Peiyi He\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nHe\, Peiyi received B.E degree from School of Integrated Circuits\, Tsinghua University\, Beijing\, China\, in 2023. He is currently pursuing the Ph.D. degree with the Department of Electrical and Electronic Engineering under the supervision of Prof. Can Li. His research interests mainly include in-memory computing\, content-addressable memory\, analog computing\, bioinformatics and computational biology. \nOrganiser\nProf. Can Li\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251120-2/ LOCATION:Online via Zoom CATEGORIES: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:20251117T140000 DTEND;TZID=Asia/Hong_Kong:20251117T150000 DTSTAMP:20260510T224204 CREATED:20251114T091828Z LAST-MODIFIED:20251114T092941Z UID:113901-1763388000-1763391600@ece.hku.hk SUMMARY:RPG Seminar – Fast Spectroscopy and Chemical-Specific Microscopy in NIR-IIc Window Based on Advanced Fiber Laser DESCRIPTION:Zoom Link: : https://hku.zoom.us/j/94746878840?pwd=YEf9BnbAPbuFS7TZl0jbE4qf5rty3N.1 \nAbstract\nThe NIR-IIc window (1600–2000 nm) offers exceptional potential for deep-tissue bioimaging. However\, progress has been hindered by the lack of suitable laser sources. To overcome the limitation\, we develop a suite of specialized laser systems tailored for the NIR-IIc region. In this talk\, several novel laser systems are introduced\, including a spectrally flat supercontinuum source for molecular discrimination\, a fiber-based oscillator for deep photoacoustic imaging of hydration dynamics\, a dual-wavelength optical parametric amplifier for multiplexed detection of materials such as microplastics\, and a dual-comb coherent Raman platform for hyperspectral validation. Collectively\, we hope that these novel laser light sources will provide new and effective solutions for exploring the NIR-IIc region. \nSpeaker\nMr. Huajun TANG\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nHuajun Tang received the B.S. degree and the master’s degree from the Huazhong University of Science and Technology (HUST)\, Wuhan\, China\, in 2016 and 2019. He is currently pursuing the Ph.D. degree in the Department of Electrical and Electronic Engineering at the University of Hong Kong\, under the supervision of Prof. Kenneth K.Y. Wong. His research interests include AI chips\, neuromorphic computing\, memory\, and VLSI design. \nOrganiser\nProf. Kenneth K.Y. Wong\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251117/ LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong CATEGORIES: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:20251117T110000 DTEND;TZID=Asia/Hong_Kong:20251117T120000 DTSTAMP:20260510T224204 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:20251117T100000 DTEND;TZID=Asia/Hong_Kong:20251117T103000 DTSTAMP:20260510T224204 CREATED:20251111T043648Z LAST-MODIFIED:20251111T043648Z UID:113864-1763373600-1763375400@ece.hku.hk SUMMARY:RPG Seminar – Scalable and Robust Energy Routing Optimization in Stochastic Vehicular Energy Network DESCRIPTION:Zoom Link: https://hku.zoom.us/j/94022031345 \nAbstract\nA vehicular energy network (VEN) enables energy transfer by leveraging electric vehicles as mobile carriers through wireless exchange across large geographic areas. A scalable and robust framework for energy routing in stochastic VENs with the objective of minimizing transmission loss is presented. The problem is formulated as a graph generalized flow optimization\, solvable to global optimality via linear programming. To ensure scalability\, a flow-guided graph reduction method is proposed\, which preserves critical supply-demand connectivity by prioritizing high-impact routes based on vehicular flow patterns. Building upon this\, a route-guided time-expanded graph construction strategy is developed to avoid exhaustive temporal replication by generating only time-relevant nodes and arcs along active routes. To address long-horizon stochasticity\, a long short-term memory-based model predictive control framework is designed\, which captures both randomness and uncertainty via data-driven forecasting and residual-aware robust correction under a rolling-horizon decomposition. The proposed methods are validated on real-world U.S. datasets\, demonstrating significant gains in computational efficiency\, scalability\, and solution robustness across both time-invariant and time-varying VENs. \nSpeaker\nMiss Yao TANG\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nYao Tang received her BEng in Electrical Engineering from Beijing Forestry University in 2019\, followed by an M.S. degree in Electrical Engineering from Hunan University. She is currently a Ph.D. candidate under the supervision of Prof. Yunhe Hou at the Department of Electrical and Electronic Engineering\, The University of Hong Kong. Her research focuses on applying AI and optimization to intelligent energy management in EV energy networks. \nOrganiser\nProf. Yunhe Hou\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251117-2/ LOCATION:Online via Zoom CATEGORIES: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:20251114T140000 DTEND;TZID=Asia/Hong_Kong:20251114T150000 DTSTAMP:20260510T224204 CREATED:20251112T031147Z LAST-MODIFIED:20251112T031147Z UID:113872-1763128800-1763132400@ece.hku.hk SUMMARY:RPG Seminar – A Hardware-Software Design Framework for SpMV Acceleration with Flexible Access Pattern Portfolio DESCRIPTION:Zoom Link: https://hku.zoom.us/j/94562380867?pwd=ZLNMv8JgAFFrSAEfnTpb6iwdFC1p3E.1 \nAbstract\nSparse matrix-vector multiplications (SpMV) are notoriously challenging to accelerate due to their highly irregular data access pattern. Although a fully customized static accel- erator design may be adequate for small problems that can fit entirely within an on-chip memory buffer\, practical SpMV problems are large and have dynamic matrix structures that cannot easily be optimized at compile time. To address this need for trade-off between flexibility and performance\, we present SPASM\, a hardware-software framework that accelerates SpMV computation using a customizable portfolio of data access pat- terns as templates and a reconfigurable hardware to support their run-time execution. SPASM extracts local data access patterns of the input matrices and derives a set of template patterns to encode these inputs. Subsequently\, a novel hardware computing structure is proposed to support vectorized computation and flexible switching between different template patterns for each tile computation. Furthermore\, SPASM leverages the global compositions of input matrices to derive hardware configuration and workload schedules that improve load balancing among the parallel processing units. Importantly\, although SPASM can optimize the pattern portfolio for a particular set of expected input matrices\, the generated hardware can flexibly be used to accelerate SpMV of different input patterns albeit with reduced performance. Experimental results show that SPASM can achieve an average 2.81× speedup compared to the state-of-the-art SpMV accelerator while keeping a relatively low customization cost. \nSpeaker\nMr. Zhenyu Wu\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nZhenyu Wu received his B.Eng from Beijing Institute of Technology in 2021. He is now a PhD student from the Department of Electronic and Electrical Engineering\, the University of Hong Kong. He is supervised by Prof. Hayden Kwok-Hay So. His research interests include domain-specific accelerator design and sparse tensor algebra. \nOrganiser\nProf. Hayden Kwok-Hay So\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20251114-1/ LOCATION:Online via Zoom CATEGORIES: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:20251110T163000 DTEND;TZID=Asia/Hong_Kong:20251110T173000 DTSTAMP:20260510T224204 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:20251107T160000 DTEND;TZID=Asia/Hong_Kong:20251107T170000 DTSTAMP:20260510T224204 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:20251107T103000 DTEND;TZID=Asia/Hong_Kong:20251107T113000 DTSTAMP:20260510T224204 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:20251105T140000 DTEND;TZID=Asia/Hong_Kong:20251105T150000 DTSTAMP:20260510T224204 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:20251025T090000 DTEND;TZID=Asia/Hong_Kong:20251025T180000 DTSTAMP:20260510T224204 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;VALUE=DATE:20250926 DTEND;VALUE=DATE:20250928 DTSTAMP:20260510T224204 CREATED:20250919T030840Z LAST-MODIFIED:20260128T063915Z UID:113431-1758844800-1759017599@ece.hku.hk SUMMARY:「港大百週年傑出中國學者計畫」──網絡與信息技術學科建設及人才培養高端論壇 DESCRIPTION:由香港大學主辦、香港大學電機電子工程系承辦、香港大學工程學院協辦，名為​「網絡與信息技術學科建設及人才培養高端論壇」活動​，旨在匯聚海內外頂尖學者，共議網安學科發展路徑，探索創新人才培養新模式。主論壇將提供高視野、前瞻性的學術引導，而方班研討廳則側重於創新表達與批判性思維的實踐鍛煉，兩者結合，將為您的科研成長帶來顯著助益。 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 主論壇\n \n \n \n \n \n 日期：9月26日（星期五）時間：14:15-17:00地點：香港大學黃麗松講堂（Rayson Huang Theatre）[HKU Map]語言：普通話 \n特邀中國工程院方濱興院士、鄭緯民院士、戴瓊海院士等多位權威專家，圍繞網絡與信息技術前沿趨勢、學科建設與人才生態發表主題演講。 \n \n 查看主論壇日流程\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 方班研討廳\n \n \n \n \n \n 日期：9月27日（星期六）時間：08:30-12:00地點：香港大學圖書館附屬樓（Library Extension Building），房間LE2-3及LE5-9 [HKU Map]語言：普通話 \n由方濱興院士親自參與指導，其他高校院士及教授現場參與，以「學生講、師生問、專家評」的深度翻轉課堂模式，開展跨校學術交流與思辨訓練。 \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主論壇日流程\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 14:15 – 14:30 \n \n \n \n \n \n \n \n \n \n \n \n 簽到入場 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 14:30 – 14:45 \n \n \n \n \n \n \n \n \n \n \n \n 香港大學副校長 致辭戴瓊海院士 致辭 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 14:45 – 14:50 \n \n \n \n \n \n \n \n \n \n \n \n 合影 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 14:50 – 15:45 \n \n \n \n \n \n \n \n \n \n \n \n 方濱興院士主題演講：人工智慧行為體保險箍 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 15:45 – 15:50 \n \n \n \n \n \n \n \n \n \n \n \n 合影／休息 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 15:50 – 16:40 \n \n \n \n \n \n \n \n \n \n \n \n 鄭緯民院士主題演講：關於人工智能大模型的三點考慮 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 16:40 – 16:45 \n \n \n \n \n \n \n \n \n \n \n \n 電機電子工程系主任 閉幕致辭 \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 16:45 – 17:00 \n \n \n \n \n \n \n \n \n \n \n \n 茶歇交流，嘉賓合影 URL:https://ece.hku.hk/events/20250926-1/ LOCATION:Rayson Huang Theatre / Library Extension Building CATEGORIES:Seminar ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/09/backdrop_P1280.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=Asia/Hong_Kong:20250924T103000 DTEND;TZID=Asia/Hong_Kong:20250924T110000 DTSTAMP:20260510T224204 CREATED:20250922T032607Z LAST-MODIFIED:20250922T032607Z UID:113449-1758709800-1758711600@ece.hku.hk SUMMARY:RPG Seminar – Laser-Assisted Interface-Welded Electrodes for Epidermal Electrophysiology Sensing DESCRIPTION:Zoom Link: https://hku.zoom.us/j/8957840635?pwd=jB4IyfmX0hTbEjn9W0LVEs31VhDw0e.1&omn=97635631185 \nAbstract\nElectrophysiological signals provide essential insights into health\, emotional responses\, and physical performance\, making their reliable collection critical for healthcare and research. However\, motion artifacts\, which cause signal distortion and compromise quality\, remain a significant challenge. In this study\, we introduce a laser-assisted interface welding (LIW) technique to avoid interface failure within electrodes\, thereby reducing motion artifacts. The developed electrode array patch consists of an adhesive layer for strong skin adhesion and a conductive layer for signal collection. Electrodes enhanced with the LIW technique exhibit exceptional toughness (114.29 J m-2) at the internal interface and improved electrical conductivity (467.8 S m-1). Compared with commercial electrodes\, the developed patch demonstrates superior conformability to human skin\, achieving an outstanding signal-to-noise ratio (>25 dB) and enabling high-quality electromyography and electrocardiography signal acquisition during motion. This work highlights the potential of the LIW technique to overcome motion artifacts\, offering a promising pathway for the reliable collection of electrophysiological signals in practical applications. \nSpeaker\nSpeaker: Mr. KANG Zhecheng\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nDing Ye received his BEng in Polymer Materials and Engineering from Northwestern Polytechnical University in 2019. He is now pursuing a MPhil degree with Leo Tianshuo Zhao in the Department of Electrical and Electronic Engineering. His research focuses on polymer hydrogel and flexible sensors. \nOrganiser\nProf. Leo Tianshuo Zhao\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20250924-1/ LOCATION:Online via Zoom CATEGORIES: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:20250918T110000 DTEND;TZID=Asia/Hong_Kong:20250918T120000 DTSTAMP:20260510T224204 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:20250916T133000 DTEND;TZID=Asia/Hong_Kong:20250916T153000 DTSTAMP:20260510T224204 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:20250916T103000 DTEND;TZID=Asia/Hong_Kong:20250916T123000 DTSTAMP:20260510T224204 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:20250912T150000 DTEND;TZID=Asia/Hong_Kong:20250912T160000 DTSTAMP:20260510T224204 CREATED:20250908T091544Z LAST-MODIFIED:20250908T091544Z UID:113375-1757689200-1757692800@ece.hku.hk SUMMARY:RPG Seminar – Fully Integrated Memristive Spiking Neural Network with Analog Neurons for High-Speed Event-Based Data Processing DESCRIPTION:Zoom Link: https://hku.zoom.us/j/99645936669 \nAbstract\nThe demand for edge artificial intelligence to process event-based\, complex data calls for hardware beyond conventional digital\, von-Neumann architectures. Neuromorphic computing\, using spiking neural networks (SNNs) with emerging memristors\, is a promising solution\, but existing systems often discard temporal information\, demonstrate non-competitive accuracy\, or rely on neuron designs with large capacitors that limit the scalability and processing speed. Here we experimentally demonstrate a fully integrated memristive SNN with a 128×24 memristor array integrated on a CMOS chip and custom-designed analog neurons\, achieving high-speed\, energy-efficient event-driven processing of accelerated spatiotemporal spike signals with high computational fidelity. This is achieved through a proportional time-scaling property of the analog neurons\, which allows them to use only compact on-chip capacitors and train directly on the spatiotemporal data without special encoding by backpropagation through surrogate gradient\, thus overcoming the speed\, scalability and accuracy limitations of previous designs. We experimentally validated our hardware using the DVS128 Gesture dataset\, accelerating each sample 50\,000-fold to a 30 µs duration. The system achieves an experimental accuracy of 93.06% with a measured energy efficiency of 101.05 TSOPS/W. We project significant future efficiency gains by leveraging picosecond-width spikes and advanced fabrication nodes. By decoupling the hardware’s operational timescale from the data’s natural timescale\, this work establishes a viable pathway for developing neuromorphic processors capable of high-throughput analysis\, critical for rapid-response edge computing applications like high-speed analysis of buffered sensor data or ultra-fast in-sensor machine vision. \nSpeaker\nSpeaker: Mr Zhu Wang\nDepartment of Electrical and Electronic Engineering\nThe University of Hong Kong \nBiography of the Speaker\nZhu Wang received the B.Eng. degree in the Department of Electronic Science and Technology at Harbin Institute of Technology\, and M.Phil. degree in the Department of Electronic Engineering at City University of Hong Kong. He is currently pursuing the Ph.D. degree in the Department of Electrical and Electronic Engineering at the University of Hong Kong\, under the supervision of Prof. Can Li. His research interests include AI chips\, neuromorphic computing\, memory\, and VLSI design. \nOrganiser\nProf. Can Li\nDepartment of Electrical and Electronic Engineering\, The University of Hong Kong \nAll are welcome. URL:https://ece.hku.hk/events/20250912-1/ LOCATION:Online via Zoom CATEGORIES: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:20250911T113000 DTEND;TZID=Asia/Hong_Kong:20250911T123000 DTSTAMP:20260510T224204 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:20250910T141500 DTEND;TZID=Asia/Hong_Kong:20250910T163000 DTSTAMP:20260510T224204 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:20250905T093000 DTEND;TZID=Asia/Hong_Kong:20250905T103000 DTSTAMP:20260510T224204 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 END:VCALENDAR