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X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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TZID:Asia/Hong_Kong
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DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20260514T093000
DTEND;TZID=Asia/Hong_Kong:20260514T103000
DTSTAMP:20260612T114430
CREATED:20260512T043316Z
LAST-MODIFIED:20260512T082808Z
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SUMMARY:Seminar on Terahertz Needle Beam Forming Transceiver Systems Based on Advanced Packaging and Massive Chiplet Integration
DESCRIPTION:Zoom Link \nhttps://hku.zoom.us/j/98399262138 \nAbstract\nFuture sensing and communication applications are converging toward a common technical objective: the development of miniaturized\, integrated\, reconfigurable\, high-speed\, and high-precision wireless hardware. These specific requirements fundamentally push the frequency of wireless systems into sub-THz regime\, where both large absolute bandwidth and electrically large apertures can be achieved within a compact physical size. In this talk\, three hardware solutions are presented\, targeting sub-THz needle beam forming transceiver systems based on advanced packaging and massive chiplet integration. First\, a 140-GHz monostatic SoC transceiver is demonstrated\, which features a low-inherent-loss full-duplexer with self-interference cancellation\, effectively mitigating beam-misalignment issues when interfacing with large THz EM apertures. Second\, to explore the feasibility of >200GHz passive antennas and interconnects within low-cost organic packages\, another 240-GHz SiP transceiver tailored for cross-polarimetric radar sensing is developed. Finally\, implementing the 240-GHz SiP transceiver as the spatial feed\, a 240-GHz 6400-element aperiodic reflectarray consists of 25 organic package modules and 400 CMOS chiplet integration is presented\, which saves 93% of the silicon area with a given radiating aperture. The full system demonstrates <0.9° beamwidth with ±50° 2D beam steering range\, and high-resolution near-field imaging. These hardware solutions and prototyping considerations provide a practical pathway toward large-scale\, distributed and reconfigurable sub-THz wireless hardware. \nSpeaker\nDr. Xibi CHEN\nDoctor of Philosophy\,\nMassachusetts Institute of Technology (MIT)\, Cambridge\, MA \nSpeaker’s Biography\nXibi CHEN received his Ph.D. degree from the Department of Electrical Engineering and Computer Science (EECS)\, Massachusetts Institute of Technology (MIT)\, Cambridge\, MA\, USA\, in 2026. He received his B.S. and M.S. degrees from Tsinghua University\, Beijing\, China\, in 2017 and 2020\, respectively. From 2015 to 2017\, he was a Research Assistant with the Microwave and Antenna Institute\, Department of Electronic Engineering\, Tsinghua University. He later became a Graduate Student Researcher in the same institute from 2017 to 2020. From 2020 to 2026\, he was a Graduate Student Researcher at EECS\, MIT. His research background includes terahertz (THz) integrated circuits and systems\, electromagnetics\, advanced packaging technologies\, large-scale phased arrays\, radar sensing\, and high-speed communications. He worked in Texas Instruments (Kilby Lab) and Intel Corporation as Summer Research Interns in 2023 and 2024\, respectively. Dr. Chen was the recipient of 2025-2026 IEEE SSCS Predoctoral Achievement Award\, and 2024 IEEE MTT-S Tom Brazil Graduate Fellowship. He also received 2025 MIT EECS MathWorks Fellowship Award\, ISSCC 2022 Student Travel Grant Award\, and Analog Devices Outstanding Student Designer Award. \nOrganiser\nProf. Kaibin HUANG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong
URL:https://ece.hku.hk/events/20260514-1/
CATEGORIES:Highlights,Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20260602T103000
DTEND;TZID=Asia/Hong_Kong:20260602T113000
DTSTAMP:20260612T114430
CREATED:20260529T100852Z
LAST-MODIFIED:20260601T084435Z
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SUMMARY:Seminar on Physics-Aware World Model for Video Generation and Embodied AI
DESCRIPTION:The seminar on “Physics-Aware World Model for Video Generation and Embodied AI” is rescheduled to begin at 10:30 am. \nAbstract\nIn AI and cognitive science\, world models are key for planning\, reasoning\, and learning from experience. An effective world model needs to: sense and learn real-world knowledge\, predict and generate real-world scenes\, reason and control according to physical laws\, and act robustly with human-in-the-loop. Prior work on world models has limited capability in representation/generation and physical awareness. We overcome these limitations through two innovations\, and towards the first open-source\, physically grounded world model from academia. First\, we develop a flow matching and DPO reinforcement learning framework to improve the continuity and physical awareness in world model representation and generation. Our world model PhyWorld achieves simultaneously best-of-the-results in physical awareness and state-of-the-art in open-source video generation. Second\, we develop a comprehensive physical awareness benchmarking and arena system. We extract comprehensively 50-60 metrics demonstrating physical law awareness of video generation and trajectory. Our comprehensive benchmark PhyGround includes video quality\, common sense\, Newtonian mechanics\, optics\, energy\, chemical\, materials\, etc.\, which is missing in literature. We generate an agent and a 9B language model for evaluating physical awareness according to these benchmarks. Last\, we describe our effort and results towards the concept of “world model for all”\, which utilises a single world model for robotic control and robot navigation\, task management\, planning\, task decomposition for high-level management and control\, as well as automatic SLAM and 3D reconstruction for environment sensing. \nSpeaker\nProf. Yanzhi WANG\nProfessor\,\nDepartment of Electrical and Computer Engineering\,\nNortheastern University \nSpeaker’s Biography\nYanzhi WANG is a Professor in the Department of Electrical and Computer Engineering and Computer Science at Northeastern University\, a senior member of IEEE. His research interests focus on real-time and energy-efficient deep learning and artificial intelligence systems\, especially on efficient large language models and large-scale generative AI systems. His research works have been published broadly in (i) machine learning conferences such as AAAI\, CVPR\, NeurIPS\, ICML\, ICCV\, ICLR\, IJCAI\, ECCV\, KDD\, ICRA\, ACM MM\, ICDM\, etc.\, (ii) architecture and system conferences such as ASPLOS\, ISCA\, MICRO\, HPCA\, CCS\, VLDB\, PLDI\, WWW\, ICS\, PACT\, CGO\, IPDPS\, INFOCOM\, ICDCS\, DAC\, ICCAD\, FPGA\, FCCM\, ISSCC\, CICC\, RTAS\, RTSS\, etc.\, and (iii) IEEE and ACM transactions. His research works have been cited 29\,000 times. He has received six Best Paper Awards and another 12 Best Paper Nominations. He has many research awards\, including the U.S. Army Young Investigator Award and other young investigator awards\, research awards from Google\, Intel\, Mathworks\, etc. His research work has been reported and cited by around 500 media. He has 18 academic descendants as tenure-track faculty members at the University of Minnesota\, University of Massachusetts Amherst\, University of Arizona\, City University of Hong Kong\, University of Georgia\, Zhejiang University\, etc. His alumni have become key contributors in Google Gemini and Alibaba Qwen 3. \nOrganiser\nProf. Kaibin HUANG\nDepartment of Electrical and Computer Engineering\,\nThe University of Hong Kong\n\nAll are welcome!
URL:https://ece.hku.hk/events/20260602-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
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DTSTART;TZID=Asia/Hong_Kong:20260609T103000
DTEND;TZID=Asia/Hong_Kong:20260609T113000
DTSTAMP:20260612T114430
CREATED:20260601T100902Z
LAST-MODIFIED:20260601T100902Z
UID:117067-1781001000-1781004600@ece.hku.hk
SUMMARY:Seminar on AI-native 6G Architecture: Distributed Intelligence and Programmable Wireless Systems
DESCRIPTION:Abstract\nThis keynote examines the architectural transition from deterministic 5G design to AI-native 6G\, where intelligence is embedded across device\, RAN\, core\, operations\, and lifecycle layers to meet extreme targets in throughput\, latency\, positioning\, and energy efficiency. Rather than treating AI as an external optimisation layer\, the talk presents 6G as a distributed and federated system in which learned policies reshape core engineering\, radio control\, and spectrum management itself. The presentation then shows how this architectural shift brings together several structural enablers and consequences: network slicing and policy control in the core\, AI-assisted beamforming in the RAN\, RIS and NTN as programmable extensions of wireless coverage\, ISAC as a sensing-capable infrastructure layer\, and ONNX/Open RAN style interoperability as part of deployable openness. It also addresses the associated constraints\, including inference-driven energy costs\, the need for explainable AI and auditability\, outcome-based licensing for dynamic spectrum access\, and the operational challenge of post-quantum security at telecom scale. The keynote argues that 6G should be understood not as a faster air interface\, but as an integrated\, programmable\, and governable cyber-physical network system whose value and risk emerge from the interaction of its components. \nSpeaker\nProf. Soumaya CHERKAOUI\nPolytechnique Montréal\, Canada \nSpeaker’s Biography\nProf. Soumaya CHERKAOUI is a Full Professor at the Department of Computer and Software Engineering at Polytechnique Montréal\, Canada. Her research interests are in wireless networks. She specialises in the convergence of machine learning and communication networks\, as well as the application of quantum technologies in future communication systems. Before joining academia as a Professor in 1999\, she worked in the industry as a project leader on aerospace-related projects. Pr. Cherkaoui has published over 200 research papers in renowned journals and conferences. She has served as a guest editor and an editorial board member for several prestigious journals\, including IEEE Journal on Selected Areas in Communications (JSAC)\, IEEE Network\, IEEE Systems\, and Computer Networks (Wiley and Elsevier). Her research has led to successful technology transfers and has been recognised with multiple accolades\, including best paper awards\, most notably at the IEEE Communications Society’s flagship conference\, IEEE ICC 2017\, with recent awards at ICCSPA 2024\, GIIS 2025\, and IEEE LCN 2024. She has played key leadership roles in major conferences\, serving as the General Chair of IEEE LCN 2019\, Technical Co-Chair of IEEE ICC 2025\, and Symposium Co-Chair for IEEE ICC 2018\, IEEE Globecom 2018\, IEEE Globecom 2015\, and IEEE ICC 2014. Additionally\, she was Chair of the IEEE Communications Society’s Technical Committee on IoT\, Ad Hoc\, and Sensor Networks (2020–2021)\, the second-largest technical committee within IEEE ComSoc. Prof. Cherkaoui is the recipient of the C.C. Gotlieb Computer Award\, the Mirela Notere Award and the IEEE Bio-Inspired Computing STC Leadership Award and was recognised as a “Star” in Networking and Communications by N2Women. She is also an IEEE Communications Society Distinguished Lecturer. \nOrganiser\nProf. Edith Cheuk Han NGAI\nDepartment of Electrical and Computer Engineering\,\nThe University of Hong Kong \nSupported By \nTam Wing Fan Innovation Wing Two\n\nAll are welcome!
URL:https://ece.hku.hk/events/20260609-1/
LOCATION:Tam Wing Fan Innovation Wing Two\, G/F\, Run Run Shaw Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
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