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X-WR-CALNAME:Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
X-ORIGINAL-URL:https://ece.hku.hk
X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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BEGIN:VTIMEZONE
TZID:Asia/Hong_Kong
BEGIN:STANDARD
TZOFFSETFROM:+0800
TZOFFSETTO:+0800
TZNAME:HKT
DTSTART:20220101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240405T140000
DTEND;TZID=Asia/Hong_Kong:20240405T150000
DTSTAMP:20260511T183615
CREATED:20240321T081304Z
LAST-MODIFIED:20250114T065546Z
UID:18119-1712325600-1712329200@ece.hku.hk
SUMMARY:RPG Seminar – Diffractive Neural Network Realized by Surface Acoustic Wave System
DESCRIPTION:Speaker\nMr. Lewei HE\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAbstract\nMatrix-vector multiplication (MVM) is a foundational operation within the architecture of deep neural networks (DNNs)\, critical for the propagation of information between layers and the overall function of the network. Recent advances in computational methodologies have sought to enhance the efficiency of MVM operations\, thereby improving the performance and applicability of DNNs across a spectrum of tasks. One innovative approach to calculate MVM is the utilization of the diffraction process inherent in wave dynamics\, which shares a mathematical resemblance with the operations of MVM.  This conceptual convergence has led to the development of diffractive neural networks\, a novel class of computational systems that employ diffraction phenomena for the execution of MVM tasks. The most common physics system to realize diffractive neural network is optical system suffering the problem of integrated on chip level. Here we propose a novel way of realizing diffractive neural network by surface acoustic wave with high integration level. The seminar will discuss the simulation method of surface acoustic wave diffractive system based on COMSOL. Additionally\, it will illustrate the difference between algorithm of diffractive neural network and tradition neural network. \nBiography of the speaker\nMr. Lewei HE is currently pursuing the MPhil Degree with the Department of Electrical and Electronic Engineering\, The University of Hong Kong (HKU). His research interests focus on simulation of diffractive surface acoustic wave system and algorithm of diffractive neural network. \nOrganizer\nProf. Shiming ZHANG
URL:https://ece.hku.hk/events/20240405-1/
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:20240403T160000
DTEND;TZID=Asia/Hong_Kong:20240403T170000
DTSTAMP:20260511T183615
CREATED:20240318T090332Z
LAST-MODIFIED:20250114T065751Z
UID:18088-1712160000-1712163600@ece.hku.hk
SUMMARY:How to write for Nature Reviews journals – Nature Reviews Bioengineering
DESCRIPTION:Abstract:\nReview and Perspective articles play a pivotal role in synthesizing\, contextualizing\, and critically analyzing the state of knowledge on timely research topics. Notably\, the editorial process at Nature Reviews journals diverges substantially from typical research journals\, something which is often not widely known in the scientific community. In this talk\, I will give an overview of the scientific publishing landscape and the editorial processes at Nature Reviews journals\, with a focus on Nature Reviews Bioengineering. I will discuss criteria used by journals to assess proposals\, including significance\, novelty and methodological rigor. I will then introduce our journal\, Nature Reviews Bioengineering\, where we publish Review\, Perspective and Comment and Down-to-business articles covering the full breadth of bioengineering\, with a particular focus on application\, translation and technology. Finally\, I’ll provide some tips on writing compelling reviews by incorporating best practices for flow\, illustrations\, explanatory boxes\, future outlooks and interdisciplinary relevance. \n\nBiography of the Speaker:\nDr. Sadra BAKHSHANDEH is a Senior Scientific Editor at Nature Reviews Bioengineering. He was trained as a mechanical engineer\, followed by a MSci in biomedical engineering from Delft University of Technology\, the Netherlands\, with a focus on biomaterials for orthopedic applications. He then completed his PhD studies and postdoc on synthetic extracellular matrices for in vitro models of cancer at the Max Planck Institute of Colloids and Interfaces in Potsdam\, Germany \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240403-1/
LOCATION:Online via Zoom
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/03/rerer.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240326T100000
DTEND;TZID=Asia/Hong_Kong:20240326T123000
DTSTAMP:20260511T183615
CREATED:20240312T043116Z
LAST-MODIFIED:20250114T065934Z
UID:18004-1711447200-1711456200@ece.hku.hk
SUMMARY:Symposium on AI for Social Good Co-organized by HKU-AI WiSe and HKU-Cambridge AI for Neurodisease Research Platform: AI for Healthy Aging: Revolutionizing Prediction and Treatment of Alzheimer’s Disease
DESCRIPTION:May we draw your attention to the following AI for Social Good event co-organized by HKU-AI WiSe and HKU-Cambridge AI for Neuro-disease Research Platform\, Faculty of Engineering\, the University of Hong Kong\, and the University of Cambridge\, sponsored partly by the US National Academy of Medicine Healthy Longevity Catalyst Award 2023.  \nYou may register below: https://forms.gle/E32UDRKgRjoWiFA76. \n \n 
URL:https://ece.hku.hk/events/20240326-1/
LOCATION:Room 102\, 1/F\, K.K. Leung Building\, The University of Hong Kong
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/03/r4t4.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240325T100000
DTEND;TZID=Asia/Hong_Kong:20240325T111500
DTSTAMP:20260511T183615
CREATED:20240318T082330Z
LAST-MODIFIED:20250114T070032Z
UID:18084-1711360800-1711365300@ece.hku.hk
SUMMARY:Enabling Decarbonisation Technologies with Power Electronics
DESCRIPTION:Speaker\nProf. Josep POU\nSchool of Electrical & Electronic Engineering\,\nNanyang Technological University (NTU)\, Singapore \nAbstract\nThis presentation will introduce some of the research developed in the Power Electronics and Applications Research Lab at NTU (PEARL@NTU). The target is to facilitate large-scale integration of renewables into the grid. This includes the design of control strategies to make solar inverters more friendly with the grid by alleviating intermittency and providing power reserve\, a multilevel-converter-based battery energy storage system that enables the use of second-life batteries for grid applications\, and a reactive power static compensator (STATCOM) that can operate with very small capacitances. The talk will also introduce the Rolls-Royce @ NTU Corporate Lab\, where future aerospace transportation technologies are designed. \nBiography of the Speaker\nProf. Josep POU received the B.S.\, M.S.\, and Ph.D. degrees in electrical engineering from the Technical University of Catalonia (UPC)-Barcelona Tech\, Spain. In 1990\, he joined the faculty of UPC as an Assistant Professor\, where he became an Associate Professor in 1993. From February 2013 to August 2016\, he was a Professor at the University of New South Wales (UNSW)\, Australia. He is currently a Professor at the Nanyang Technological University (NTU)\, Singapore\, where he is a Cluster Director of Power Electronics at the Energy Research Institute at NTU (ERI@N) and co-Director of the Rolls-Royce @ NTU Corporate Lab. He spent two years as a visiting professor in the Center for Power Electronics Systems\, Virginia Tech\, USA\, and one year in the Australian Energy Research Institute\, UNSW\, Australia. He has authored 477 published technical papers and is a co-inventor of 8 patents. His research interests include power electronics\, renewable energy\, energy storage\, power quality\, HVDC transmission\, and transportation electrification. \nHe is an IEEE Fellow. He is Associate Editor of the IEEE Journal of Emerging and Selected Topics in Power Electronics. He was co-Editor-in-Chief and Associate Editor of the IEEE Transactions on Industrial Electronics. He received the 2018 IEEE Bimal Bose Award for Industrial Electronics Applications in Energy Systems. \nAll are welcome!
URL:https://ece.hku.hk/events/20240325/
LOCATION:Room CB-601J\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/03/20240325-banner_1280.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240323T185000
DTEND;TZID=Asia/Hong_Kong:20240323T203000
DTSTAMP:20260511T183615
CREATED:20240319T010323Z
LAST-MODIFIED:20250114T070152Z
UID:18089-1711219800-1711225800@ece.hku.hk
SUMMARY:HKU-AI WiSe: AI for Social Good - A Fireside Chat on AI for Social Good
DESCRIPTION:May we draw your attention to the following AI for Social Good evening event by HKU-AI WiSe\, Faculty of Engineering\, the University of Hong Kong\, partly funded by RGC-TRS. \nOnline Registration: https://forms.gle/UJZLhk61xLi8mDBq7 \n \nOnline Registration: https://forms.gle/UJZLhk61xLi8mDBq7 \n \nOnline Registration: https://forms.gle/UJZLhk61xLi8mDBq7 \nRSVP! Looking forward to welcoming you at the event on 23 March\, 2024 (Saturday).
URL:https://ece.hku.hk/events/20240323-1/
LOCATION:Lecture Theatre CB-A\, G/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/03/t5t5t.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240319T093000
DTEND;TZID=Asia/Hong_Kong:20240319T104500
DTSTAMP:20260511T183615
CREATED:20240228T082539Z
LAST-MODIFIED:20250114T070331Z
UID:17957-1710840600-1710845100@ece.hku.hk
SUMMARY:Simultaneously Transmitting And Reflecting Surface (STARS) for 360° Coverage
DESCRIPTION:In this talk\, the novel concept of simultaneously transmitting and reflecting surfaces (STARS) will be introduced. First\, the STAR basics will be introduced. In particular\, the fundamental signal modelling\, performance limit characterization\, practical operating protocols\, and joint beamforming design will be discussed. Then\, the coupled phase-shift STAR model\, AI-enabled STARS\, and channel estimation methods will be focused. Furthermore\, several promising case studies of employing STARS will be put forward\, including STAR-NOMA\, spatial analysis for STARS\, federated learning with STARS\, and STARS enabled integrated sensing and communications (ISAC). Finally\, research opportunities and problems as well as commercial progress of STARS. \nBiography of the speaker: \nDr. Yuanwei LIU is an Associate Professor at the School of Electronic Engineering and Computer Science\, Queen Mary University of London. His research interests include next-generation multiple access\, integrated sensing and communications reconfigurable intelligent surface\, and near-field communications. He is a Fellow of IEEE\, a Fellow of AAIA\, Web of Science Highly Cited Researcher since 2021 to present. He is listed as one of 35 Innovators Under 35 China in 2022 by MIT Technology Review. He serves as an IEEE Communication Society Distinguished Lecturer\, an IEEE Vehicular Technology Society Distinguished Lecturer\, the Academic Chair for the Next Generation Multiple Access Emerging Technology Initiative\, the rapporteur of ETSI Industry Specification Group on Reconfigurable Intelligent Surfaces\, and the UK representative for the URSI Commission C on Radio Communication Systems and Signal Processing. He received IEEE ComSoc Outstanding Young Researcher Award for EMEA in 2020. He received the 2020 IEEE Signal Processing and Computing for Communications (SPCC) Technical Committee Early Achievement Award\, IEEE Communication Theory Technical Committee (CTTC) 2021 Early Achievement Award. He received IEEE ComSoc Outstanding Nominee for Best Young Professionals Award in 2021. He is the co-recipient of the Best Student Paper Award in IEEE VTC2022-Fall\, the Best Paper Award in ISWCS 2022\, the 2022 IEEE SPCC-TC Best Paper Award and the IEEE ICCT 2023 Best Paper Award. He serves as the Co-Editor-in-Chief of IEEE ComSoc TC Newsletter\, an Area Editor of IEEE Communications Letters\, an Editor of IEEE Communications Surveys & Tutorials\, IEEE Transactions on Wireless Communications\, IEEE Transactions on Vehicular Technology\, and IEEE Transactions on Network Science and Engineering. He serves as the (leading) Guest Editors for Proceedings of the IEEE/IEEE JSAC/JSTSP/Network/TGCN. \nAll are welcome!
URL:https://ece.hku.hk/events/20240319-1/
LOCATION:Room CB-601J\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240318T000000
DTEND;TZID=Asia/Hong_Kong:20240318T000000
DTSTAMP:20260511T183615
CREATED:20240306T015653Z
LAST-MODIFIED:20250114T070444Z
UID:17977-1710720000-1710720000@ece.hku.hk
SUMMARY:Capturing Life: Optical Microscopy for in vivo Deep Tissue Imaging at High Spatiotemporal Resolution
DESCRIPTION:Optical microscopy has become an indispensable tool for non-invasive\, high-resolution in vivo imaging of living organisms. Its capability to provide insights into real-time physiological and pathological processes within the body underscores its significance in bioscience and medicine. However\, conventional optical microscopy methods have certain limitations. For instance\, multiphoton fluorescence microscopy\, the method of choice for in vivo imaging through scattering tissue such as the mammalian brains\, delivers excellent resolution but falls short in speed for capturing rapid biological activities\, such as blood flow dynamics. On the other hand\, optical coherence tomography (OCT)\, a label-free deep-tissue imaging method\, stands as a powerful instrument in contemporary optometry clinics\, but its high cost limits its broad use\, especially in lower-income communities. In this presentation\, I will share my research on the development of high-speed multiphoton fluorescence microscopy and cost-effective OCT for brain and eye imaging\, respectively\, through the utilization of both optical engineering and computational methods. \n  \nBiography of the speaker: \nDr. Guanghan MENG\, currently a postdoctoral scholar in the Department of Electrical Engineering and Computer Science at the University of California\, Berkeley\, focuses on advancing high-speed\, high-resolution fluorescence\, and label-free microscopy technologies for deep tissue imaging in vivo. Having earned her PhD from the same university\, her doctoral research spanned the disciplines of Molecular and Cell Biology and Physics\, primarily concentrating on enhancing two-photon fluorescence microscopy for mouse brain imaging. At present\, she is working on computational label-free imaging with a specific interest in the human eye. She has been recognized with various best presentation awards at scientific conferences and is a recipient of the Berkeley Center for Innovation in Vision and Optics (CIVO) postdoctoral fellowship. She is also an invited lecturer at the 17th Edition of the Frontiers in Neurophotonics Summer School in Quebec City\, Canada in 2024. \nAll are welcome!
URL:https://ece.hku.hk/events/20230318-1/
LOCATION:Room CB-601J\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/03/r44t.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240315T173000
DTEND;TZID=Asia/Hong_Kong:20240315T183000
DTSTAMP:20260511T183615
CREATED:20240304T065035Z
LAST-MODIFIED:20250220T074356Z
UID:17970-1710523800-1710527400@ece.hku.hk
SUMMARY:Career Talk - CHOICES IN FUTURE CAREER: Entrepreneurship\, Research\, or Banking?
DESCRIPTION:Have you ever considered exploring alternative paths for your future career choices? This presents a unique opportunity to gain more insight in that regard. \nThe Department has extended an invitation to an entrepreneur and researcher\, Dr. David Ng\, and a board member of banks\, Dr. David Wong who will share their valuable experience with you. By attending\, you will have the chance to broaden your perspective on career options. \nBiography of the speakers: \nDr. David Ng\, our Adjunct Assistant Professor\, holds a Ph.D. in Electrical Engineering from HKU EEE\, where he developed his engineering skills. He is an active member of both HKIE and IEEE\, and his contributions in the field have led to the acquisition of over 20 patents from the United States and China throughout his career. Prior to his Ph.D.\, Dr. Ng obtained a bachelor’s degree in electronic engineering from HKUST. He further enhanced his knowledge by pursuing an MSc degree in Electronic & Information Engineering and an Executive MBA (EMBA) degree from CityU. Dr. Ng gained valuable industry experience during his time at Motorola Semiconductor\, Arizona\, USA. \nWith more than 20 years of impressive work experience in the high-tech industry as an entrepreneur and architectural IC design researcher\, Dr. Ng has founded technology companies focused on Integrated Circuit (IC) design. These ventures received funding from multinational companies and Venture Capitals after his tenure at ASTRI (Hong Kong Government Agency)\, ON Semiconductor (a NASDAQ-listed semiconductor company)\, and Motorola (an NYSE-listed Telecommunications Company). Dr. Ng has a proven track record of successfully raising millions of US dollars from the HK Government and various industries to support next-generation IC design technologies. During his time at ASTRI\, he played a crucial role in assisting a client in getting listed on the Hong Kong GEM Board by licensing his team’s intellectual property for production. \nDr. David Wong\, See Hong has served as a Non-Executive and Non-Independent Director since June 10\, 2023\, after nine years as a Non-Executive and Independent Director. With over 30 years of experience in the banking sector\, he possesses extensive knowledge in treasury and financial products. \nFrom 2008 to 2013\, Dr. Wong held the position of Deputy Chief Executive at Bank of China (Hong Kong) Group\, overseeing various financial market businesses like Global Markets\, Global Transaction Banking\, Investment Management\, Insurance\, Asset Management\, and other capital market-related activities. Dr. Wong has held board positions at the Energy Market Authority and the Civil Service College in Singapore and served as a Customer Advisory Board Member of Thomson Reuters. \nCurrently\, Dr. Wong is a board member at Frasers Property Limited\, China Merchants Bank Co.\, Ltd\, and EC World Asset Management Pte Ltd. He serves as Chairman of Halftime Hong Kong Limited and is a Finance Management Committee member of the Hong Kong Management Association. \nDr. Wong holds a Bachelor’s Degree in Business Administration from the University of Singapore and a Master of Science degree in Investment Management from the Hong Kong University of Science and Technology. He has been recognized as a Financial Industry Certified Professional by the Institute of Banking and Finance\, Singapore. \nAll are welcome! \nDetails: https://ece.hku.hk/elink/career.html
URL:https://ece.hku.hk/events/career-talk-choices-in-future-career-entrepreneurship-research-or-banking/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Career Talks,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240314T160000
DTEND;TZID=Asia/Hong_Kong:20240314T180000
DTSTAMP:20260511T183615
CREATED:20240221T062420Z
LAST-MODIFIED:20250114T072504Z
UID:17944-1710432000-1710439200@ece.hku.hk
SUMMARY:Image quality transfer and democratization of MRI
DESCRIPTION:My talk will focus on Image Quality Transfer (Alexander et al Neuroimage 2017; Tanno et al Neuroimage 2021; Lin et al ISMRM 2021)\, and its role in international efforts to democratize MRI expertise and capability\, such as the CAMERA network https://www.medrxiv.org/content/10.1101/2022.05.02.22274588\nv1.full. The technique aims to use machine learning to estimate high quality images\, e.g. from a powerful experimental scanner\, from lower quality images\, e.g. acquired on a standard hospital scanner or low-field systems. I will talk through the history of development of these ideas\, show some of the latest results\, speculate about future opportunities\, and describe some challenges and observations of implementing these ideas in LMIC scenarios. I will also cover briefly some other aspects of my work at UCL on microstructure imaging\, e.g. NODDI (Zhang et al Neuroimage 2012) for neuroimaging and VERDICT (Panagiotaki et al Cancer Research 2013) for cancer imaging\, as well as disease progression modelling using techniques such as the subtype and stage algorithm (Young et al Nature Comms 2018) for mapping subtypes of chronic disease such as Alzheimer’s disease. \nBiography of the speaker: \nProfessor Alexander is the Director of the UCL Centre for Medical Image Computing (CMIC) at University College London (UCL) and Professor of Imaging Science in UCL’s Department of Computer Science.  His expertise is in computational modelling\, machine learning\, imaging and image analysis. He has a BA in Mathematics from the University of Oxford (1993)\, an MSc in Computer Science from UCL (1994)\, and a PhD in Computer Science from UCL (1998). He worked as a post-doc at the University of Pennsylvania until 2000 when he returned to London to take up an academic position. He became full professor in 2009\, Director of CMIC in 2015\, senior fellow of the ISMRM in 2017\, and fellow of the Royal Academy of Engineering in 2022 and IEEE in 2023.\n\nAll are welcome.
URL:https://ece.hku.hk/events/image-quality-transfer-and-democratization-of-mri/
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/2024/02/Seminar-s-banner.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240313T093000
DTEND;TZID=Asia/Hong_Kong:20240313T103000
DTSTAMP:20260511T183615
CREATED:20240307T030817Z
LAST-MODIFIED:20250114T072600Z
UID:17987-1710322200-1710325800@ece.hku.hk
SUMMARY:Design and Modulation of Multifunctional Artificial Synaptic Devices
DESCRIPTION:In recent years\, synaptic electronic devices have gained significant attention for their applications in neural morphological computing and peripheral neural sensing simulations. It is of great significance to further enhance the functionality of these devices to replicate more complex neural transmission processes. The presenter will provide a brief overview of recent advancements in this field and discuss his work in the design and modulation of artificial synapse devices through reasonable integrating of optoelectronic materials\, interface engineering\, and heterojunction adjusting. Furthermore\, he will delve into the functional design of artificial synaptic devices across diverse application scenarios\, and share his perspective on next work plan for advancing synaptic devices. \n  \nBiography of the speaker: \nDr. Yao NI was born in 1994 and obtained his Ph.D. from Nankai University in 2023. He currently serves as a Lecturer at Guangdong University of Technology. His research primarily focuses on neuromorphic electronic devices and systems. As the first (co-first) author and corresponding author\, Dr. NI has published more than 20 SCI papers in internationally renowned scientific and technological journals\, including Nat. Commun.\, ACS Nano\, Adv. Sci.\, SmartMat\, Adv. Funct. Mater.\, Nano Energy\, Nano Letters\, etc. His collaborative papers have been cited more than 800 times\, and several of his works have received active media coverage. Additionally\, Dr. NI has authored 2 chapters in English monographs and filed more than 10 invention patents. He serves as an editor and reviewer for multiple domestic and international journals (conferences) and has been invited to participate in academic conferences multiple times\, receiving honors such as the Excellent Academic Report Award and Excellent Poster Award. He is a member of professional societies such as the Institute of Electrical and Electronics Engineers (IEEE)\, Chinese Association of Automation (CAA)\, China Institute of Communications (CIC)\, and Chinese Chemical Society (CCS). \nAll are welcome!
URL:https://ece.hku.hk/events/20240313-1/
LOCATION:Online via Zoom
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/02/Seminar-s-banner.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240308T110000
DTEND;TZID=Asia/Hong_Kong:20240308T123000
DTSTAMP:20260511T183615
CREATED:20240301T023428Z
LAST-MODIFIED:20250114T072651Z
UID:17962-1709895600-1709901000@ece.hku.hk
SUMMARY:Exploring Trustworthy Machine Learning under Imperfect Data
DESCRIPTION:Trustworthy machine learning is one of emerging and critical topics in modern machine learning\, since most real-world data are easily imperfect\, such as online transactions\, healthcare\, cyber-security\, and robotics. Intuitively\, trustworthy intelligent system should behave more human-like\, which can learn and reason from imperfect data including labels\, features\, systems and prompts. Therefore\, in this talk\, I will introduce trustworthy machine learning from several human-inspired views\, including reliability\, robustness\, adaptability and safety. Specifically\, reliability will consider uncertain cases\, namely reliable learning with noisy labels. Robustness will discuss adversarial conditions\, namely robust learning with adversarial features. Adaptability will explore the algorithm interactions\, namely adaptive learning with federated systems. Safety will investigate harmful prompts in foundation models\, namely safe reasoning with jailbreak attacks. Furthermore\, I will introduce the newly established Trustworthy Machine Learning and Reasoning (TMLR) Group at Hong Kong Baptist University. \nBiography of the speaker: \nDr. Bo HAN is an Assistant Professor in Machine Learning at Hong Kong Baptist University and a BAIHO Visiting Scientist at RIKEN AIP\, where his research focuses on machine learning\, deep learning\, foundation models and their applications. He was a Visiting Faculty Researcher at Microsoft Research and a Postdoc Fellow at RIKEN AIP. He has co-authored two machine learning monographs by MIT Press and Springer Nature. He has served as Area Chairs of NeurIPS\, ICML\, ICLR\, UAI and AISTATS. He has also served as Action Editors and Editorial Board Members of JMLR\, MLJ\, TMLR\, JAIR and IEEE TNNLS. He received Outstanding Paper Award at NeurIPS\, Notable Area Chair at NeurIPS\, Outstanding Area Chair at ICLR\, and Outstanding Associate Editor at IEEE TNNLS. \nAll are welcome!
URL:https://ece.hku.hk/events/exploring-trustworthy-machine-learning-under-imperfect-data/
LOCATION:Room CB-601J\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240304T160000
DTEND;TZID=Asia/Hong_Kong:20240304T170000
DTSTAMP:20260511T183615
CREATED:20240228T081116Z
LAST-MODIFIED:20250114T072753Z
UID:17953-1709568000-1709571600@ece.hku.hk
SUMMARY:Towards Generalizable and Robust Multimodal AI for Healthcare
DESCRIPTION:Artificial Intelligence (AI) is catalyzing a paradigm shift in healthcare\, promising to reshape the landscape of patient care. At the heart of this transformation is medical imaging\, where AI-enabled technologies hold substantial promise for precise and personalized image-based diagnosis and treatment. Despite these advances\, these models often underperform at real-world deployment\, particularly due to the heterogeneous data distributions and varying modalities in healthcare applications. In this talk\, I will introduce our work dedicated to tackling these real-world challenges to advance model generalizability and multimodal robustness. First\, I will show how we can leverage generative networks and model adaptation to generalize models under data distribution shifts. Next\, I will describe how to achieve robust multimodal learning with missing modalities and with imaging and non-imaging clinical information. Finally\, I will present our work that extends to large-scale datasets and more diverse modalities based on foundation model for generalizable multimodal representation learning. \nBiography of the speaker: \nDr. Cheng CHEN is a postdoc research fellow at the Center for Advanced Medical Computing and Analysis\, Harvard Medical School. She obtained her Ph.D. degree in Computer Science and Engineering at The Chinese University of Hong Kong in 2021. She received her M.S. and B.S. degrees from Johns Hopkins University and Zhejiang University\, respectively. Her research interests lie in the interdisciplinary area of AI and healthcare\, with a focus on generalizable\, robust\, and multimodal medical image analysis. She has over 25 papers published at top AI and medical imaging venues\, reaching over 2300 Google Scholar citations with an h-index of 16. Her first-authored papers have been recognized as an ESI “Highly cited paper”\, selected as oral presentations\, and received travel awards from AAAI and MICCAI. In addition\, she has been named one of the Global Top 80 Chinese Young Female Scholars in AI and won the MICCAI Federated Brain Tumor Segmentation Challenge. \nAll are welcome.
URL:https://ece.hku.hk/events/20240304-1/
LOCATION:Room CB-601J\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/02/Seminar-s-banner.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240304T150000
DTEND;TZID=Asia/Hong_Kong:20240304T165000
DTSTAMP:20260511T183615
CREATED:20240222T062850Z
LAST-MODIFIED:20250114T072855Z
UID:17945-1709564400-1709571000@ece.hku.hk
SUMMARY:Running a net-zero grid in 2024: experiences from the Australian "real-world lab"
DESCRIPTION:With deeper and deeper penetration of variable renewable energy sources (RES) and distributed energy resources (DER) across the world\, new challenges are emerging in terms of their grid and market integration. In this lecture we will illustrate these challenges from a techno-economic perspective\, with focus on security and reliability requirements when operating power systems and markets with ultra-deep penetration of RES and DER\, and with the support of real experiences from Australia\, and particularly South Australia\, which has already exhibited net-zero grid operation in the past couple of years. We will then discuss several technical\, commercial and regulatory solutions and opportunities that are being deployed or considered\, ranging from widespread adoption of both highly distributed and large-scale batteries to the development of “clean super-power” plans based on green hydrogen investment. \nBiography of the speaker: \n\nPierluigi Mancarella is the Chair Professor of Electrical Power Systems at The University of Melbourne\, Australia\, and Professor of Smart Energy Systems at The University of Manchester\, UK. \nHe received his MSc (2002) and PhD (2006) degrees from the Politecnico di Torino\, Italy\, worked as a post-doc at Imperial College London\, UK\, has held visiting positions in the US (NREL)\, France (Ecole Centrale de Lille)\, Chile (University of Chile)\, and China (Tsinghua University)\, and will be the 2024 Otto Monsted Visiting Professor at the Danish Technical University (DTU)\, Denmark. \nPierluigi’s research interests include techno-economic modelling of low-carbon grids\, multi-energy systems\, energy system planning under uncertainty\, and reliability and resilience of future networks. He has been involved in/led more than 100 research projects worldwide\, has been actively engaged with energy policy in the UK\, Europe and Australia\, and is author of several books and of over 400 research publications and reports. \nPierluigi is a Fellow of the IEEE; an IEEE Power and Energy Society Distinguished Lecturer; a Senior Editor of the IEEE Transactions on Power Systems; an Editor of the IEEE Transactions on Energy Markets\, Policy and Regulation; the Convenor of the Cigre C6/C2.34 WG on “Flexibility provision from distributed energy resources”; and the inaugural Chair of the WG on Energy of the IEEE European Public Policy Initiative. \nPierluigi was awarded the 2017 veski Innovation Fellowship by the Victorian Government for his “FlexCity” project on multi-energy urban virtual power plants\, and an international Newton Prize 2018 for his UK-Chile Newton-Picarte project on power system resilience. He also led the Melbourne Energy Institute’s work “Power system security assessment of the future National Electricity Market” for the Australian Chief Scientist’s “Finkel Review”. He has recently been working closely with the Australian Energy Market Operator (AEMO)\, the Australian Energy Market Commission (AEMC)\, National Grid ESO (UK)\, and a number of other industry stakeholders in the development of distributed energy marketplaces\, new power system security\, reliability and resilience services and markets\, and new methodologies and tools for energy system planning under uncertainty. \nPierluigi is the Australian Director of the recently announced USA-UK-Australia Global Centre in Climate Change and Clean Energy “Electric Power Innovation for a Carbon-Free Society (EPICS)”\, co-led with Johns Hopkins University (USA) and Imperial College London (UK). \n\n\nAll are welcome.
URL:https://ece.hku.hk/events/running-a-net-zero-grid-in-2024-experiences-from-the-australian-real-world-lab/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240201T110000
DTEND;TZID=Asia/Hong_Kong:20240201T120000
DTSTAMP:20260511T183615
CREATED:20240125T060320Z
LAST-MODIFIED:20250114T072932Z
UID:107412-1706785200-1706788800@ece.hku.hk
SUMMARY:Key technology and application of cable-driven parallel robots
DESCRIPTION:As an essential part of intelligent manufacturing\, R & D\, fabricating\, and application of robots become the important manifestation to show the national scientific and technological innovation ability as well as the industrial level. The cable-driven parallel robot (CDPR) combines cable drive technology and parallel mechanism theory\, which inherits the high acceleration and load capacities of the rigid parallel robots\, and further obtains significant improvements in workspace\, lightweight\, and energy efficiency. The CDPR embodies the cutting-edge trend of the fusion of rigid and flexible mechanisms\, reflects the advanced lightweight design\, and is a crucial direction for robot science and technology development. The CDPR has an irreplaceable important role in the fields of industry\, national defense\, science\, and technology. This talk will take “China Sky Eye” (Five-hundred-meter Aperture Spherical radio Telescope) as an example to introduce the research on technologies related to large-space CDPRs based on the rigid-flexible series configuration\, explain the innovation of high-speed CDPRs based on the rigid-flexible parallel configuration\, and illustrate the application of the above technologies in industry. The core advantages and the recent development focus of the CDPR are summarized as an end. \nBiography of the speaker: \nProfessor Zhufeng Shao is an associate professor of the Mechanical Engineering Department at Tsinghua University\, senior member of the China Society of Mechanical Engineering\, member of National Industrial Foundation Expert Committee\, editorial board member of the Defence Technology journal and member of national professional standards technical committee. He is also the director of the intelligent equipment and system research center at Tsinghua University WUXI Research Institute of Applied Technologies. His principal research interests are high-performance robots and intelligent manufacturing. He has published 42 SCI and 38 EI papers\, issued 6 approved national standards on intelligent manufacturing\, and obtained 48 authorized Chinese invention patents and 16 software copyrights. He has won the China Patent Silver Award\, the second prize of Natural Science of the Ministry of Education\, the special prize and the second prize of China Machinery Industry Science and Technology Award.\n\nAll are welcome.
URL:https://ece.hku.hk/events/key-technology-and-application-of-cable-driven-parallel-robots/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240125T100000
DTEND;TZID=Asia/Hong_Kong:20240125T110000
DTSTAMP:20260511T183615
CREATED:20240117T065641Z
LAST-MODIFIED:20250114T074426Z
UID:17934-1706176800-1706180400@ece.hku.hk
SUMMARY:High-power GHz femtosecond fiber laser technologies and frontier applications
DESCRIPTION:Fiber lasers have been known as compact and robust laser sources. When operating in the femtosecond-pulse regime with high repetition rates (HRRs)\, particularly at a level of GHz\, they open new opportunities for industrial and scientific applications\, such as high-speed ablation-cooled material removal\, ultrafast measurement\, low-photodamage biophotonics\, etc. Among various schemes of generating HRR fs fiber laser\, fundamentally mode-locking in ultrashort Fabry-Pérot (FP) fiber cavities is a promising method for generating fs pulses at repetition rates of several-to-tens GHz. Despite these exciting opportunities\, further efforts are still required for improving the repetition rate\, average power\, pulse width\, wavelength range\, as well as the noise performance and long-term stability. In this talk\, I will present the latest progress on the high-power GHz femtosecond fiber lasers. In the meanwhile\, the application exploration in the fields of ultrafast measurement\, micro-machining and biological imaging will also be briefly discussed. \nBiography of the speaker: \nDr. Xiaoming Wei received his B.S. and M.S. degrees from South China University of Technology\, China\, in 2009 and 2012\, respectively\, and PhD degree from the University of Hong Kong in 2015. He received the postdoctoral training from both the University of Hong Kong (OCT\, 2015 – April\, 2017) and Caltech (May\, 2017 – Aug.\, 2019)\, then he joined the Department of Physics and Optoelectronics\, South China University of Technology. So far\, he has published more than 100 papers in peer-reviewed journals\, including Nature Communications\, Science Advances\, Light: Science & Applications\, Optics Letters\, etc\, and filed more than 50 patents in the field of ultrafast optics. His research interests include high-power femtosecond fiber lasers and their applications in the fields of ultrafast measurement\, micromachining and biophotonics.\n\nAll are welcome.
URL:https://ece.hku.hk/events/high-power-ghz-femtosecond-fiber-laser-technologies-and-frontier-applications/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/02/Seminar-s-banner.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240124T110000
DTEND;TZID=Asia/Hong_Kong:20240124T123000
DTSTAMP:20260511T183615
CREATED:20240111T025050Z
LAST-MODIFIED:20250114T074434Z
UID:17930-1706094000-1706099400@ece.hku.hk
SUMMARY:Critical Issues in the Electrohydrodynamic Inject Printing – Examples of printing fluorescent quantum dots
DESCRIPTION:Micro-printing is a good way to manufacture patterning structures in modern manufacture\, which has been widely used in fields\, e.g. micro-LED display\, benefiting from the high material utilization. The electrohydrodynamic inject printing (EHD-IP) is proven to be with the highest spatial resolution among various micro-printing techniques. Still\, the ink control and homogeneity are two main obstacles EHD-IP are facing before its possible fully commercialization. In this talk\, by taking the example of printing color conversion layer for micro-LED displays\, I will introduce new designs of EHD specialized inks that have been developed in our research group recently. (a) The dual non-polar solvent perovskite QD colloidal ink for EHD-IP; (b) Three dimensional micro-pillars arrays manufactured by EHD-IP; (c) Dual ligands passivated red perovskite QDs inks. During the introduction of these work\, I would like to discuss some fundamental principles\, such as the differences in dynamics between inks employing polar and non-polar solvents\, interaction between ligands and solvent and its effect on colloidal stability\, how to decoupling designs of functional QDs and E-field driven-able ink\, etc. These issues are universally applied to various kinds of EHD specialized inks and determine the final quality of EHD-IP. \nBiography of the speaker: \nYue received his B.Sc. in the Department of Physics at Southeast University. He received his Ph.D. degree from the Department of Electronic Science at Xiamen University. He is currently an associate professor in the Department of Electronic Science\, Xiamen University. His research scope includes a) Micro-LED display technology; b) Electrohydrodynamic inkjet printing for quantum dot color conversion layers; c) GaN and AlGaN based semiconductor material and devices and the optoelectronic properties; d) All-inorganic and hybrid perovskite quantum dots and the optoelectronic properties. As first and/or corresponding author\, he published more than 20 papers on journals such as Adv. Mat.\, Adv. Opt. Mat.\, Small\, Appl. Phys. Lett.\, Chinese Chemical Letters\, etc. He hosted fundings like NSF of China\, NSF and cooperation funding of Fujian Province\, etc.\n\nAll are welcome.
URL:https://ece.hku.hk/events/critical-issues-in-the-electrohydrodynamic-inject-printing-examples-of-printing-fluorescent-quantum-dots/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/02/Seminar-s-banner.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240123T163000
DTEND;TZID=Asia/Hong_Kong:20240123T180000
DTSTAMP:20260511T183615
CREATED:20240112T064937Z
LAST-MODIFIED:20250114T074441Z
UID:17931-1706027400-1706032800@ece.hku.hk
SUMMARY:New prospects for group IV and III-V Materials for optoelectronic Applications
DESCRIPTION:Nowadays\, there is a large effort to find a monolithic solution for photonics and electronics. The main purpose is to integrate materials which have high carrier mobility and high photonic performance for optoelectronic components. In many cases\, a 3D integration is required where electrons are processing the data and photons are communicating the data in a chip. In this field of research\, materials such as Ge\, GeSi or GeSn have attracted attention due to their excellent electronic and photonic properties. These materials have been applied in the channel of transistors as well in active regions for detection and lasing of Infrared light. Ge\, GeSi and GeSn have demonstrated excellent performance in near and short wavelength infrared (SWIR) regions. Although\, a large effort has been spent on group IV materials for laser application but so far there is no operating laser at room temperature. There are also some interests for III-V growth on Si for photonic application. The control of defect density is a vital issue for good performance. This invited talk will present the challenges for the integration of group IV materials as well as III-V materials on Si for optoelectronics devices. Issues such as epitaxy\, material quality\, strain engineering\, structure designs for SWIR detectors and lasers are discussed in detail. \nBiography of the speaker: \nProfessor Henry Homayoun Radamson is from Sweden\, he got bachelor from Stockholm University\, later got Master and PhD from Linkoping University in 1996\, Institute of Physics and Measurement Techniques. Between 1997-2016\, he worked for Royal Institute of Technology in Sweden\, Department of Electrical components and circuits as a Senior Researcher. Henry got invited to China through 1000-talent project since 2016 and worked in Institute of Microelectronics of the Chinese Academy of Sciences (IMECAS). In 2019\, Prof. Radamson was invited as chief Scientist in Guangdong Greater Bay Area Institute of Integrated Circuit and System (GIICS) and he became Fellow of European Academy of Sciences same year. So far\, he has almost 300 publications in Journals like ASC Nano\, Nano Letters\, Physical Review B\, Applied Physics Letter\, IEEE Electron Device Letters\, IEEE Transactions on Electron Devices\, etc. He has also written 4 books like CMOS past present and future.He has got many awards like Swedish quality innovation\, First award in 2019; Swedish venture Cup award\, Innovation contest\, 10 Best awards in 2011; Talent Award Guangzhou\, March 2023; Friendship Award in China\, March 12\, 2023; Best Tutor Award\, University of Chinese Academy of Sciences 2021; ZhuliYuehua Teacher Award\, University of Chinese Academy of Sciences 2020; Best Course Award\, University of Chinese Academy of Sciences 2020; Best Teacher Award\, University of Chinese Academy of Sciences\, 2019; Foreign Talent Award\, China\, 2018; Best Teacher Award\, Reykjavik University\, Iceland\, 2008. So Far\, His research field focuses on semiconductor materials and process. Until 2022\, he has successfully made Germanium-based short wave infrared chips with commercial quality and significant price advantage compared with InGaAs material chip. He is also working with Terahertz chips and laser materials which have wide application in the market.\n\nAll are welcome.
URL:https://ece.hku.hk/events/new-prospects-for-group-iv-and-iii-v-materials-for-optoelectronic-applications/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240116T163000
DTEND;TZID=Asia/Hong_Kong:20240116T173000
DTSTAMP:20260511T183615
CREATED:20240110T060851Z
LAST-MODIFIED:20250114T074547Z
UID:17923-1705422600-1705426200@ece.hku.hk
SUMMARY:Modelling and Design of Smart Radio Environments
DESCRIPTION:Since 2019\, reconfigurable intelligent surface (RIS) has attracted a lot of interests from both academia and industry. In this talk\, Professor Jie Zhang will first introduce their pioneering work on Smart Radio Environments back to 2012 in a 2.2 million Euros research project titled “Wireless Friendly Energy Efficient Buildings (WiFEEB)” in which frequency selective surfaces\, intelligent walls and reconfigurable intelligent structures were studied. Then\, he will give an introduction of their ground-breaking work on the establishment of a theoretical building wireless performance (BWP) evaluation framework that can be used to quantify the wireless performance of a building layout (i.e.\, given a building design/floorplan\, tells how “wireless friendly” it is). Next\, he will briefly introduce the progress on RIS simulation that they have made in a South Korea – UK joint R&D project titled “AI-powered Reconfigurable Intelligent Surface (AIRIS)”.  Finally\, he will discuss how to use the BWP evaluation framework to analyse the impact of smart radio environments on the indoor wireless network performance such as the deployment of RIS. \nBiography of the speaker: \nProfessor Jie Zhang has held the Chair in Wireless Systems at the Department of Electronic and Electrical Engineering\, University of Sheffield\, Sheffield\, U.K.\, on a part-time basis\, since January 2011. He is also the Founder\, Board Director and  Chief Scientific Officer of Ranplan Wireless\, Cambridge\, U.K.\, a public company listed on Nasdaq First North and a professor at HIT Shenzhen since 2023. Ranplan Wireless produces a suite of world leading indoor and the first joint indoor-outdoor radio access network planning tool — Ranplan Professional\, which is being used over 300 industrial and academic customers including all the top 5 telecom equipment vendors\, the world’s largest mobile operators\, and leading research organisations. Along with his students and colleagues\, he has pioneered research in small cell and heterogeneous network and published some of the landmark papers and book on these topics\, widely used by both academia and industry. Since 2010\, he and his team have also developed ground-breaking work in smart radio environment and building wireless performance modelling\, evaluation and optimisation\, the key concepts of which were introduced in a paper titled “Fundamental Wireless Performance of a Building”\, IEEE Wireless Communications\, 29(1)\, 2022. His Google scholar citations are in excess of 9000 with an H-index of 41. He received a PhD in Industrial Automation from East China University of Science and Technology\, Shanghai\, China\, in 1995. Prior to joining the University of Sheffield\, he had studied/worked with Imperial College London\, Oxford University\, and University of Bedfordshire\, reaching a status of Senior Lecturer\, Reader and Professor in 2002\, 2005 and 2006\, respectively.\n\nAll are welcome.
URL:https://ece.hku.hk/events/modelling-and-design-of-smart-radio-environments/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/02/Seminar-s-banner.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240110T110000
DTEND;TZID=Asia/Hong_Kong:20240110T120000
DTSTAMP:20260511T183615
CREATED:20240102T063048Z
LAST-MODIFIED:20250114T074608Z
UID:17912-1704884400-1704888000@ece.hku.hk
SUMMARY:Machine Learning for Real-Time Constrained Optimization: The Case of Optimal Power Flows
DESCRIPTION:Optimization problems subject to hard constraints are common in time-critical applications such as autonomous driving and wireless communication. However\, existing iterative solvers often face difficulties in solving these problems in real-time. In this talk\, we focus on one such problem – the critical optimal power flow (OPF) problem in power system operation. We develop DeepOPF as a neural network (NN) approach to solve OPF problems directly\, orders of magnitude faster than state-of-the-art iterative solvers. The idea is to employ NN’s approximation capability to learn the input-solution mapping of the OPF problem (or any constrained problem). Thus\, one can pass the input to the NN and receive a quality solution instantly. A fundamental issue\, however\, is to ensure NN solution feasibility with respect to the hard constraints\, which is non-trivial due to inherent NN prediction errors. To this end\, we present two approaches\, predict-and-reconstruct and homeomorphic projection\, to ensure NN solution strictly satisfies the equality and inequality constraints. In particular\, homeomorphic projection is a low-complexity scheme to guarantee NN solution feasibility for optimization over a general set homeomorphic to a unit ball\, covering all compact convex sets and certain classes of nonconvex sets. The idea is to (i) learn a minimum distortion homeomorphic mapping between the constraint set and a unit ball using an invertible NN (INN)\, and then (ii) perform a simple bisection operation concerning the unit ball so that the INN-mapped final solution is feasible with respect to the constraint set with minor distortion-induced optimality loss. We prove the feasibility guarantee and bound the optimality loss under mild conditions. Simulation results\, including those for non-convex AC-OPF problems in power grid operation\, show that homeomorphic projection outperforms existing methods in solution feasibility and run-time complexity\, while achieving similar optimality loss. We will also discuss open issues in machine learning for solving constrained puzzles. \nBiography of the speaker: \nMinghua received his B.Eng. and M.S. degrees from the Department of Electronic Engineering at Tsinghua University. He received his Ph.D. degree from the Department of Electrical Engineering and Computer Sciences at University of California Berkeley. He is a Professor of School of Data Science\, City University of Hong Kong. He received the Eli Jury award from UC Berkeley in 2007 (presented to a graduate student or recent alumnus for outstanding achievement in the area of Systems\, Communications\, Control\, or Signal Processing) and The Chinese University of Hong Kong Young Researcher Award in 2013. He also received several best paper awards\, including IEEE ICME Best Paper Award in 2009\, IEEE Transactions on Multimedia Prize Paper Award in 2009\, ACM Multimedia Best Paper Award in 2012\, IEEE INFOCOM Best Poster Award in 2021\, and ACM e-Energy Best Paper Award in 2023. Storage codes co-invented by Minghua have been incorporated into Microsoft Windows and Azure Cloud Storage\, serving hundreds of millions of users. His recent research interests include online optimization and algorithms\, machine learning in power system operation\, intelligent transportation\, distributed optimization\, delay-critical networking\, and capitalizing the benefit of data-driven prediction in algorithm/system design. He is an ACM Distinguished Scientist and an IEEE Fellow.
URL:https://ece.hku.hk/events/machine-learning-for-real-time-constrained-optimization-the-case-of-optimal-power-flows/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20231222T160000
DTEND;TZID=Asia/Hong_Kong:20231222T170000
DTSTAMP:20260511T183615
CREATED:20231218T081037Z
LAST-MODIFIED:20250114T074745Z
UID:17890-1703260800-1703264400@ece.hku.hk
SUMMARY:RPG Seminar – High Speed Quantitative Phase and Polarization Microscopy for Zebrafish In Vivo Blood Cell Imaging
DESCRIPTION:Quantitative phase and polarization microscope (QPPI) is a useful label-free microscopic tool in revealing the quantitative biophysical information of cells\, such as cell shape\, dry mass and their subcellular distribution. However\, the current existing QPPI system could only offer a low imaging speed which is not sufficient to observe the dynamic activities of the live animal samples\, which is very important in understanding the disease developments and drug treatment effects. One example would be on the zebrafish leukaemia model. Fast imaging speed with high content images could be able to help monitor the in vivo blood flowing cells\, which provide the dynamic information of the cancer situations and drug effects after the different treatments. To boost the imaging speed of the QPPI system\, one possible solution is to combine the QPPI imaging technique with the existing developed ultrafast imaging system which is the Free-space Angular-chirp-enhanced Delay (FACED). This could help boost the imaging speed up to kHz which is sufficient to observe any zebrafish blood cell movements and reveal more information on the leukaemia as well as the effect of drugs. \nZoom Link :\nhttps://hku.zoom.us/j/5701095284?pwd=SUJYUFg1Q2pybUZhNE5WbnBqUXBSdz09 \nBiography of the speaker:\n\nRicky Hui received the BEng in Biomedical Engineering (BME) in 2022 in The University of Hong Kong (HKU) and is currently pursuing the MPhil Degree with the Department of Electrical and Electronic Engineering\, The University of Hong Kong (HKU). His research interests focus on ultrafast imaging\, volumetric imaging\, and quantitative label-free imaging techniques. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-high-speed-quantitative-phase-and-polarization-microscopy-for-zebrafish-in-vivo-blood-cell-imaging/
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:20231222T150000
DTEND;TZID=Asia/Hong_Kong:20231222T160000
DTSTAMP:20260511T183615
CREATED:20231218T075938Z
LAST-MODIFIED:20250114T075012Z
UID:17887-1703257200-1703260800@ece.hku.hk
SUMMARY:RPG Seminar – Large-scale single-cell morphological profiling on a spinning arrayed optofluidic platform
DESCRIPTION:Morphological profiling in imaging microscopy can reveal biological cells characteristics. However\, current image-based assay relays heavily on costly and extensive amount of fluorescent antibodies and is limited by the trade-off between the image resolution and scalability of the experiment. Therefore\, here we presented a spinning arrayed optofluidic platform to achieve live cell\, label free\, large-scale and high-resolution imaging. We demonstrated the stability of the system can achieve long-term imaging monitoring for at least 30 mins and further validated that the platform shows minimal effects on cells health based of a panel of cell-health assays. The application of the platform and morphological profiling was demonstrated through a drug screening analysis on two ling cancer cell lines with four drugs having five different concentrations\, which we observed that drug-concentration applied to lung-cancer cells showed obvious morphological profile shifts. Our profiling technique also showed the potential on understanding the viral entry mechanisms and impact on label-free cell morphology from quantitative phase imaging on CRISPR-based cell-cell fusion assay involving human ACE2 receptor cells and SARS-CoV-2 spike protein expression cells. The results show new and valuable insights on drug treatment and disease- and gene-related phenotypes. \nZoom Link :\nhttps://hku.zoom.us/j/95494140198?pwd=WEtVcEtFRjdzdGdacmFReFZLWkhmUT09\nMeeting ID: 954 9414 0198\nPassword: 217678 \nBiography of the speaker:\n\nVictor Wong received the BEng in medical engineering in 2019 and is currently pursuing the Ph.D. degree with the Department of Electrical and Electronic Engineering\, The University of Hong Kong (HKU). His research interests focus on ultrafast imaging\, single cell analysis\, and morphological profiling. He was also awarded the Research Postgraduate Student Innovation Award in 2022/23 established by Graduate School and the Technology Transfer Office. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-large-scale-single-cell-morphological-profiling-on-a-spinning-arrayed-optofluidic-platform/
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:20231222T140000
DTEND;TZID=Asia/Hong_Kong:20231222T150000
DTSTAMP:20260511T183615
CREATED:20231218T080705Z
LAST-MODIFIED:20250114T074904Z
UID:17889-1703253600-1703257200@ece.hku.hk
SUMMARY:RPG Seminar – Neural computing in random resistive memory
DESCRIPTION:Arrays\, graphs\, and point sets are fundamental data organization forms in mathematics\, with significant applications in scientific computing and engineering problems like signal processing\, molecular discovery\, and 3D vision. However\, the progress of digital circuitry\, limited by Moore’s Law\, has slowed down\, impeding the advancement of these problems. The increasing data and computational demands have amplified the von Neumann bottleneck in traditional computing systems\, necessitating urgent improvements in energy efficiency\, latency\, and computational capacity. Novel memory-based computing paradigms\, such as resistive memories\, have made progress in addressing these challenges. However\, resistive memories suffer from high power consumption and delay during write operations\, due to the need for high voltages to form conductive filaments. Randomness in filament shape and size also introduces inaccuracies. To overcome these issues\, we propose a co-design approach that minimizes programming/write operations in machine learning systems handling arrays\, graphs\, and point sets. This method improves system efficiency and guarantees performance. Validation on tasks involving arrays\, graphs\, and point sets demonstrates superior task performance and significant energy reduction compared to traditional computing systems. These research opens doors to future in-memory computing acceleration system design. \nZoom Link :\nhttps://hku.zoom.us/j/98133426720 \nBiography of the speaker:\n\nShaocong Wang is a fourth-year Ph.D. candidate at IMSC lab\, Department of Electrical and Electronic Engineering\, The University of Hong Kong (HKU). His supervisor is  Dr. Zhongrui Wang. His research interest includes computing-in-memory and analogue computing. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-neural-computing-in-random-resistive-memory/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20231222T110000
DTEND;TZID=Asia/Hong_Kong:20231222T120000
DTSTAMP:20260511T183615
CREATED:20231214T090837Z
LAST-MODIFIED:20250114T075053Z
UID:17884-1703242800-1703246400@ece.hku.hk
SUMMARY:RPG Seminar – Single-pulse optogenetic perturbation of thalamo-cortical networks reveals rsfMRI architecture
DESCRIPTION:Resting-state fMRI (rsfMRI) has emerged as the most valuable\, non-invasive imaging technique to map long-range\, brain-wide functional connectivity networks. Recently\, dynamic rsfMRI network segregation and integration have been shown to facilitate and modulate diverse cognitive functions. Such dynamics are structural-functional hierarchically organized and have been observed across a range of temporal scales\, spanning from days or hours\, to minutes. Converging studies postulate that critical transient states and their transition processes subserve such functional architecture of rsfMRI networks. \nHowever\, previous studies using either rsfMRI measurements only (i.e.\, during awake/sleep state) or task-based fMRI with conventional stimulation paradigms (i.e.\, block-designed/pulse trains) fail to clearly dissect transient/seconds-level reorganization of rsfMRI architecture upon stimulations. Here\, we propose to implement a single-pulse stimulation design to exert minimum influence on spontaneous activities (e.g.\, occurrence/intensity of spontaneous neural events) while modulating rsfMRI transient states and transition processes. \nZoom Link :\nhttps://hku.zoom.us/j/7179232708?omn=92069441167 \nBiography of the speaker:\n\nLinshan Xie obtained her B.Eng degree in Electronic Science and Technology from the University of Electronic Science And Technology Of China in 2020. She is now pursuing PhD in the Department of Electrical and Electronic Engineering at the University of Hong Kong under the supervision of Prof. Ed X Wu and Dr. Alex T.L. Leong. Her research interests focus on fMRI application in neuroscience\, including task-based (optogenetic) and resting-state fMRI acquisition and analysis. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-single-pulse-optogenetic-perturbation-of-thalamo-cortical-networks-reveals-rsfmri-architecture/
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:20231222T110000
DTEND;TZID=Asia/Hong_Kong:20231222T120000
DTSTAMP:20260511T183615
CREATED:20231213T063326Z
LAST-MODIFIED:20250114T075645Z
UID:17876-1703242800-1703246400@ece.hku.hk
SUMMARY:RPG Seminar – Video Demoireing with Relation-Based Temporal Consistency
DESCRIPTION:Moire patterns\, appearing as color distortions\, severely degrade the image and video qualities when filming a screen with digital cameras. Considering the increasing demands for capturing videos\, we study how to remove such undesirable moire patterns in videos\, namely video demoireing. To this end\, we introduce the first hand-held video demoireing dataset with a dedicated data collection pipeline to ensure spatial and temporal alignments of captured data. Further\, a baseline video demoireing model with implicit feature space alignment and selective feature aggregation is developed to leverage complementary information from nearby frames to improve frame-level video demoireing. More importantly\, we propose a relation-based temporal consistency loss to encourage the model to learn temporal consistency priors directly from ground-truth reference videos\, which facilitates producing temporally consistent predictions and effectively maintains frame-level qualities. Extensive experiments manifest the superiority of our model. \nZoom Link :\nhttps://hku.zoom.us/j/95468941119?pwd=UVpSUGowM3F2OXlwUzN6ajhvWHVQUT09\nMeeting ID: 954 6894 1119\nPassword: 336484 \nBiography of the speaker:\n\nPeng Dai is a fourth-year Ph.D. candidate at CVMI Lab\, Department of Electrical and Electronic Engineering\, The University of Hong Kong (HKU). His supervisor is Dr. Xiaojuan Qi. His research interest includes computer vision and computer graphics. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-video-demoireing-with-relation-based-temporal-consistency/
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:20231222T100000
DTEND;TZID=Asia/Hong_Kong:20231222T110000
DTSTAMP:20260511T183615
CREATED:20231218T080324Z
LAST-MODIFIED:20250114T074936Z
UID:17888-1703239200-1703242800@ece.hku.hk
SUMMARY:RPG Seminar – Can 3D Vision-Language Models Truly Understand Natural Language?
DESCRIPTION:Rapid advancements in 3D vision-language (3D-VL) tasks\, such as 3D Visual Question Answering (3D-VQA) and 3D Visual Grounding (3D-VG)\, have opened up new avenues for human interaction with embodied agents or robots using natural language. Despite this progress\, we find a notable limitation: existing 3D-VL models exhibit heightened sensitivity to language input\, struggling to handle sentences with minor stylistic changes. This observation raises the critical question: “Can 3D vision-language models truly understand natural language?” We first propose a language robustness task for systematically assessing 3D-VL models across various tasks\, benchmarking their performance when presented with different language style variants. We propose the first 3D Language Robustness Dataset\, designed based on the characteristics of human language\, to facilitate the systematic study of robustness. Our comprehensive evaluation uncovers a significant drop in the performance of all existing models across various 3D-VL tasks. Even the state-of-the-art 3D-LLM fails on some variances. Further in-depth analysis suggests that the existing model fails to align the feature space\, which also stems from the low diversity of the existing dataset. We also propose a plug-and-play training free pre-alignment module driven by LLM\, which can improve language robustness. The data will be available to facilitate further research. \nZoom Link :\nhttps://hku.zoom.us/j/96527514816\nMeeting ID: 965 2751 4816 \nBiography of the speaker:\n\nWeipeng DENG received his B.Eng. of Computer Science from South China University of Technology. Currently\, he is pursuing his Ph.D. degree at the University of Hong Kong. His work is focused on how to leverage language to assist vision-language system. His research interests include deep learning\, large language model\, prompt\, vision-language model. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-can-3d-vision-language-models-truly-understand-natural-language/
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:20231222T100000
DTEND;TZID=Asia/Hong_Kong:20231222T110000
DTSTAMP:20260511T183615
CREATED:20231213T064055Z
LAST-MODIFIED:20250114T075508Z
UID:17878-1703239200-1703242800@ece.hku.hk
SUMMARY:RPG Seminar – CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation
DESCRIPTION:Existing methods for adapting Neural Radiance Fields (NeRFs) to scene changes require extensive data capture and model retraining\, which is both time-consuming and labor-intensive. In this paper\, we tackle the challenge of efficiently adapting NeRFs to real-world scene changes over time using a few new images while retaining the memory of unaltered areas\, focusing on the continual learning aspect of NeRFs. To this end\, we propose CL-NeRF\, which consists of two key components: a lightweight expert adaptor for adapting to new changes and evolving scene representations and a conflict-aware knowledge distillation learning objective for memorizing unchanged parts. We also present a new benchmark for evaluating Continual Learning of NeRFs with comprehensive metrics. Our extensive experiments demonstrate that CL-NeRF can synthesize high-quality novel views of both changed and unchanged regions with high training efficiency\, surpassing existing methods in terms of reducing forgetting and adapting to changes. \nZoom Link :\nhttps://hku.zoom.us/j/3164938755 \nBiography of the speaker:\n\nXiuzhe Wu received her B.Eng. and M.Eng degrees at Tongji University. Currently\, she is pursuing Ph.D. degree at the University of Hong Kong\, advised by Dr. Xiaojuan Qi. Her research interests focus on 3D vision. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-cl-nerf-continual-learning-of-neural-radiance-fields-for-evolving-scene-representation/
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:20231221T140000
DTEND;TZID=Asia/Hong_Kong:20231221T150000
DTSTAMP:20260511T183615
CREATED:20231214T090442Z
LAST-MODIFIED:20250114T075128Z
UID:17883-1703167200-1703170800@ece.hku.hk
SUMMARY:RPG Seminar – Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning
DESCRIPTION:Federated learning (FL) inevitably confronts the challenge of system heterogeneity in practical scenarios. To enhance the capabilities of most model-homogeneous FL methods in handling system heterogeneity\, we propose a training scheme that can extend their capabilities to cope with this challenge. In this seminar\, we commence our study with a detailed exploration of homogeneous and heterogeneous FL settings and discover three key observations: (1) a positive correlation between client performance and layer similarities\, (2) higher similarities in the shallow layers in contrast to the deep layers\, and (3) the smoother gradient distributions indicate the higher layer similarities. Building upon these observations\, we introduce InCo Aggregation that leverages internal cross-layer gradients\, a mixture of gradients from shallow and deep layers within a server model\, to augment the similarity in the deep layers without requiring additional communication between clients. Furthermore\, our methods can be tailored to accommodate model-homogeneous FL methods such as FedAvg\, FedProx\, FedNova\, Scaffold\, and MOON\, to expand their capabilities to handle the system heterogeneity. Copious experimental results validate the effectiveness of InCo Aggregation\, spotlighting internal cross-layer gradients as a promising avenue to enhance the performance in heterogeneous FL. \nZoom Link :\nhttps://hku.zoom.us/j/93707944044?pwd=VEtnNkVzYnNlY2IrUWR0UjhwVGV5UT09 \nBiography of the speaker:\n\nYun-Hin Chan received his B.Eng. of Software Engineering from Sun Yat-sen University. Currently\, he is pursuing his Ph.D. degree at the University of Hong Kong. His work is focused on how to solve practical challenges in federated learning\, such as communication efficiency and system heterogeneity. His research interests include deep learning\, distributed optimization\, federated learning\, knowledge distillation\, and transfer learning. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-internal-cross-layer-gradients-for-extending-homogeneity-to-heterogeneity-in-federated-learning/
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20231221T110000
DTEND;TZID=Asia/Hong_Kong:20231221T120000
DTSTAMP:20260511T183615
CREATED:20231213T085231Z
LAST-MODIFIED:20250114T075234Z
UID:17882-1703156400-1703160000@ece.hku.hk
SUMMARY:RPG Seminar – Modelling AC Loss in Superconductors via Integral Method
DESCRIPTION:Superconductors can potentially be used in electrical machines in future electric aircraft\, since superconductors can increase the power density of electrical machines. When superconductors are carrying ac or are subject to an alternating magnetic field\, they experience ac loss. AC loss affects the efficiency of the machines and the cooling power needed\, which has implications for the mass of the overall system of the electric aircraft. The integral method can model superconductors that are carrying arbitrary ac and under an arbitrary external magnetic field. This talk will review the integral method in the literature\, and explain how the integral method can be used to model superconductors in an electrical machine. In addition\, it will also explain how the integral method can be used to model in 2D cables made of superconducting tapes that are coupled (electrically connected at the ends of the cable or along the whole length of the tapes). \nZoom Link :\nhttps://hku.zoom.us/j/99033734395\nMeeting ID: 990 3373 4395 \nBiography of the speaker:\n\nChung Tin Calvin Chow received the B.A. and M.Eng. degrees in engineering from the University of Cambridge\, Cambridge\, U.K.\, both in 2020\, with specialization in areas including control and information engineering. He is currently pursuing a Ph.D. degree in electrical and electronic engineering with the Department of Electrical and Electronic Engineering\, The University of Hong Kong\, Hong Kong\, SAR\, China. He was a visitor at Karlsruhe Institute of Technology\, Germany\, for around 5 months in 2022-2023 and at the University of Strathclyde\, UK\, for around 6 months in 2023. His research interests include superconducting machines and drives\, superconductor modelling and experimentation. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-modelling-ac-loss-in-superconductors-via-integral-method/
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:20231220T170000
DTEND;TZID=Asia/Hong_Kong:20231220T180000
DTSTAMP:20260511T183615
CREATED:20231213T084857Z
LAST-MODIFIED:20250114T075316Z
UID:17881-1703091600-1703095200@ece.hku.hk
SUMMARY:RPG Seminar – Deep learning enabled fast 3D brain MRI at 0.055 tesla
DESCRIPTION:In recent years\, there has been an intensive development of portable ultralow-field magnetic resonance imaging (MRI) for low-cost\, shielding-free\, and point-of-care applications. However\, its quality is poor and scan time is long. We propose a fast acquisition and deep learning reconstruction framework to accelerate brain MRI at 0.055 tesla. The acquisition consists of a single average three-dimensional (3D) encoding with 2D partial Fourier sampling\, reducing the scan time of T1- and T2-weighted imaging protocols to 2.5 and 3.2 minutes\, respectively. The 3D deep learning leverages the homogeneous brain anatomy available in high-field human brain data to enhance image quality\, reduce artifacts and noise\, and improve spatial resolution to synthetic 1.5-mm isotropic resolution. Our method overcomes low-signal barrier\, reconstructing fine anatomical structures that are reproducible within subjects and consistent across two protocols. It enables fast and quality whole-brain MRI at 0.055 tesla\, with potential for widespread biomedical applications. \nZoom Link :\nhttps://hku.zoom.us/j/93224346406\nMeeting ID: 932 2434 6406 \nBiography of the speaker:\n\nChristopher Man received his bachelor degree in the University of Hong Kong and is currently pursuing PhD in the University of Hong Kong\, under the supervision of Prof. Ed X. Wu. His research interests include MRI image reconstruction and deep learning. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-deep-learning-enabled-fast-3d-brain-mri-at-0-055-tesla/
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:20231220T160000
DTEND;TZID=Asia/Hong_Kong:20231220T170000
DTSTAMP:20260511T183615
CREATED:20231213T084213Z
LAST-MODIFIED:20250114T075441Z
UID:17879-1703088000-1703091600@ece.hku.hk
SUMMARY:RPG Seminar – Pushing the limits of ultra-low-field MRI by dual-acquisition super-resolution
DESCRIPTION:Recent development of ultra-low-field (ULF) MRI presents opportunities for low-power\, EMI shielding-free\, and portable clinical applications of MRI. However\, the imaging performance of these emerging ULF MRI scanners remains limited due to its three orders of magnitude weaker main magnetic field\, resulting in the poor signal-to-noise ratio. Advancements in deep learning have opened new frontiers for improving ULF MRI image quality. In this seminar\, we present a novel dual-acquisition deep learning method for enhancing spatial resolution and suppressing noise/artifacts of 3D ULF brain MRI images acquired at our custom-built 0.055T brain MRI scanner.. \nZoom Link :\nhttps://hku.zoom.us/j/98172884162?pwd=VWVmeE5DWjhvcGJIeUZGdTBtRWdzQT09 \nBiography of the speaker:\n\nMan Hin Lau (Vick) obtained his MEng degree in Biomedical Engineering from Imperial College London in 2019. After a year working as a research assistant at HKU\, he is now pursuing a PhD degree with Prof Ed X Wu in the Department of Electrical and Electronic Engineering. His research focuses on the application of deep learning techniques to MRI image processing and reconstruction. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-pushing-the-limits-of-ultra-low-field-mri-by-dual-acquisition-super-resolution/
CATEGORIES:Seminar
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END:VCALENDAR