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X-WR-CALNAME:Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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BEGIN:VTIMEZONE
TZID:Asia/Hong_Kong
BEGIN:STANDARD
TZOFFSETFROM:+0800
TZOFFSETTO:+0800
TZNAME:HKT
DTSTART:20230101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240508T103000
DTEND;TZID=Asia/Hong_Kong:20240508T113000
DTSTAMP:20260513T031747
CREATED:20240429T062517Z
LAST-MODIFIED:20250114T063611Z
UID:18468-1715164200-1715167800@ece.hku.hk
SUMMARY:RPG Seminar – Transformer-based Architectures for Automated Annotation in 3D Point Clouds
DESCRIPTION:Abstract\nManual annotation of 3D point clouds is notoriously labor-intensive\, prompting the need for automated solutions. Existing automated annotation methods\, however\, are typically complex and may neglect the crucial inter-object feature relationships that are informative for annotating challenging samples. In response\, we introduce two end-to-end Transformer-based models\, CAT and CAT++\, which are streamlined to serve as automated 3D-box labelers. These models leverage a minimal set of human annotations to produce precise 3D box annotations from 2D boxes. Our architecture employs a dual encoder strategy: a local intra-object encoder and a global inter-object encoder\, both utilizing self-attention mechanisms to process sequence and batch dimensions. The intra-object encoder captures point-level interactions within objects\, while the inter-object encoder discerns feature relationships across objects\, enhancing scene comprehension. The advanced CAT++ model incorporates a Hierarchical-interleaved encoding scheme and an implicit neural representation\, further refining the annotation process. Benchmarking experiments on the KITTI and nuScenes datasets demonstrate our models’ superior performance over current state-of-the-art methods\, particularly in annotating complex scenarios encompassing all hard samples. \nSpeaker\nMs. Xiaoyan QIAN\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nBiography of the speaker\nMs. Xiaoyan QIAN received the B.Eng. degree in Industrial Engineering from the Zhejiang University of Technology\, Zhejiang\, China. She is currently a Ph.D. candidate in the Department of Electrical and Electronic Engineering at the University of Hong Kong\, under the supervision of Dr. N Wong and Prof. SC Tan. Her current research interests mainly focus on 3D point clouds\, weakly supervised 3D object detection\, and auto-driving. \nOrganizer\nProf. N. WONG \nAll are welcome.
URL:https://ece.hku.hk/events/20240508-2/
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:20240514T140000
DTEND;TZID=Asia/Hong_Kong:20240514T150000
DTSTAMP:20260513T031747
CREATED:20240503T092811Z
LAST-MODIFIED:20250114T063407Z
UID:18489-1715695200-1715698800@ece.hku.hk
SUMMARY:RPG Seminar – Complex-valued Transformer for Wireless Communications
DESCRIPTION:Meeting ID: 892 6022 4678\nPassword: n9QxYg \nAbstract\nIn recent years\, attention-based models\, particularly those employing the transformer structure\, have exhibited exceptional performance in tasks such as natural language processing\, computer vision\, and wireless communication\, among others. Notably\, most of these transformer frameworks rely on real-valued operations\, where inputs\, outputs\, and trainable parameters are real numbers\, even in tasks involving complex-valued domains.\nComplex-valued neural networks (CVNN) have emerged as a powerful approach for addressing problems associated with the complex-valued nature of input data. However\, the application of complex-valued transformers remains largely unexplored within the field of wireless communication\, where most task inputs\, such as received symbols and channel coefficients\, are intrinsically complex-valued. \nThis seminar aims to unveil the potential of complex-valued transformers for complex-valued domain tasks in wireless communications\, specifically focusing on channel estimation in single-input-single-output system and device activity detection in grant-free massive access scenario. To this end\, we propose tailored complex-valued transformer designs that incorporate complex-valued attention mechanisms for both tasks. In particular\, the proposed frameworks exploit the relationship between the real and imaginary parts of signals as implicit constraints\, while capturing temporal and spatial correlations of complex-valued input features. Moreover\, we introduced a novel complex-to-real layer to convert the complex-valued feature into the probabilistic representation for the activity detection task. \nNumerical results demonstrate the superiority of the proposed complex-valued transformers framework compared with other deep-learning based methods and optimization approaches. \nSpeaker\nMiss Leng Yang\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nBiography of the speaker\nMiss Leng Yang received the B.Eng. degree in Electronic and Information Science and Technology from Fudan University in 2022. She is currently pursuing the MPhil degree with the Department of Electrical and Electronic Engineering\, The University of Hong Kong\, Hong Kong. \nOrganizer\nProf. Yik-Chung WU \nAll are welcome.
URL:https://ece.hku.hk/events/20240514-1/
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:20240514T140000
DTEND;TZID=Asia/Hong_Kong:20240514T150000
DTSTAMP:20260513T031747
CREATED:20240503T094824Z
LAST-MODIFIED:20250114T063447Z
UID:18490-1715695200-1715698800@ece.hku.hk
SUMMARY:RPG Seminar – Image Augmented Multimodal Autolabeller for 3D Object Detection
DESCRIPTION:Abstract\nRecently deep learning methods have gained groundbreaking success in many areas\, including autonomous driving and 3D object detection. Powerful neural networks are proposed and yield human-comparable ability after being trained from large datasets. Nonetheless\, the annotation procedure is time-consuming and tedious. To automate the annotation process\, we proposed two methods called MAP-Gen and MTrans\, respectively. Leveraging both image and point cloud modalities\, the two methods can effectively alleviate the sparsity problem of point clouds and hence generate high-quality pseudo labels. \nSpeaker\nMr. Liu Chang\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nBiography of the speaker\nMr. Liu Chang received his B.Eng. degree in Computer Engineering from the University of Hong Kong. He is currently a Ph.D. student supervised by Dr. N. Wong and Prof. Edmund Y. Lam\, at the Department of Electrical and Electronic Engineering\, University of Hong Kong. His current research interests include 3D Vision\, Point Cloud\, Multi-modal Neural Networks\, and NLP. \nOrganizer\nProf. N. WONG
URL:https://ece.hku.hk/events/20240514-2/
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:20240514T140000
DTEND;TZID=Asia/Hong_Kong:20240514T150000
DTSTAMP:20260513T031747
CREATED:20240506T013049Z
LAST-MODIFIED:20250114T063519Z
UID:18492-1715695200-1715698800@ece.hku.hk
SUMMARY:RPG Seminar – Memristor Enabling Efficient Combinatorial Optimization with Quantum-inspired Parallel Annealing
DESCRIPTION:Abstract\nCombinatorial optimization problems are prevalent in various fields\, but obtaining exact solutions remains challenging due to the combinatorial explosion with increasing problem size. Special-purpose hardware such as Ising machines\, particularly memristor-based analog Ising machines\, have emerged as promising solutions. However\, existing simulate-annealing-based \nimplementations have not fully exploited the inherent parallelism and analog storage/processing features of memristor crossbar arrays. This work proposes a quantum-inspired parallel annealing method that enables full parallelism and improves solution quality\, resulting in significant speed and energy improvement when implemented in analog memristor crossbars. We experimentally solved tasks\, including unweighted and weighted Max-Cut and traveling salesman problem\, using our integrated memristor chip. The quantum inspired parallel annealing method implemented in memristor-based hardware has demonstrated significant improvements in time- and energy- efficiency compared to previously reported simulated annealing and Ising machine implemented on other technologies. This is because our approach effectively exploits the natural parallelism\, analog conductance states\, and all-to-all connection provided by memristor technology\, promising its potential for solving complex optimization problems with greater efficiency. \nSpeaker\nMr. Mingrui JIANG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nBiography of the speaker\nMr. Mingrui JIANG received the B.E. degree from School of Optical and Electronic Information\, Huazhong University of Science and Technology\, Wuhan\, China\, in 2020. He is currently pursuing the Ph.D. degree with the Department of Electrical and Electronic Engineering\, The University of Hong Kong\, Hong Kong SAR. His research interests include analog signal processing\, analog in-memory computing and neuromorphic computing based on emerging memory devices (e.g.\, memristors). \nOrganizer\nProf. Can LI \nAll are welcome.
URL:https://ece.hku.hk/events/20240514-3/
LOCATION:Online via Zoom
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240515T160000
DTEND;TZID=Asia/Hong_Kong:20240515T170000
DTSTAMP:20260513T031747
CREATED:20240304T071147Z
LAST-MODIFIED:20250114T072111Z
UID:17971-1715788800-1715792400@ece.hku.hk
SUMMARY:Microneedle-based Skin Patch for Transdermal Drug Delivery and Biosensing
DESCRIPTION:Microneedles (MNs) are an emerging platform for transdermal applications including drug delivery\, insulin delivery\, vaccination\, biosensing\, disease diagnosis\, and cosmeceutical industry. Their advantages lie in their easy-to-use\, pain-free\, minimally invasive\, and self-administrable features. This overcomes the skin barrier to enhance transdermal delivery of drugs and biomolecules with different physicochemical properties in vitro\, ex vivo and in vivo. In this talk\, Prof. Xu will share microneedle technologies developed in his lab for meeting a wide range of medical needs\, including keloid treatment and prevention\, obesity treatment\, dental and eye disease treatment\, and immune therapies. He will also present his envision in utilizing MN platform for the in-situ monitoring of physiological signals. \nBiography of the speaker: \nProf. Chenjie XU got his PhD\, Master\, and BS from Brown University (2009)\, HKUST (2004)\, Nanjing University (2002) respectively. He had conducted research at Stanford University (2005)\, Brigham and Women’s Hospital (2009-2012)\, and Nanyang Technological University (2012-2019). Currently\, he is an associate professor of biomedical engineering at the City University of Hong Kong. Prof. XU is dedicated to the development of transdermal drug delivery formulations and devices (especially nucleic acid-based nanoparticles and microneedle-based skin patches). He is well known for the development of skin patch for keloid treatment\, anti-obese skin patch\, skin patch for skin interstitial fluid extraction etc. He has published more than 140 peer-reviewed articles (citation is 11k with H index of 45)\, edited two books\, holding 10 international patents\, and found two spin-offs. His research is supported by a wide range of public and private foundations including Singapore Minister of Education\, Singapore A*Star\, Continental Corp (German)\, Bill & Melinda Gates Foundation\, Hong Kong University Grants Committee\, National Natural Science Foundation of China\, etc. \nAll are welcome
URL:https://ece.hku.hk/events/20240315/
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/2024/03/20240315-banner.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240516T110000
DTEND;TZID=Asia/Hong_Kong:20240516T120000
DTSTAMP:20260513T031747
CREATED:20240507T081518Z
LAST-MODIFIED:20250114T063319Z
UID:18499-1715857200-1715860800@ece.hku.hk
SUMMARY:RPG Seminar – Domain-Specific Efficient Neural Network Architecture Design
DESCRIPTION:Abstract\nAI models significantly impact our daily lives\, but their high performance brings the challenge of model complexity. Deploying these models on edge devices poses additional challenges\, including power consumption\, memory storage and latency constraints. In this seminar\, we will delve into designing efficient neural network architectures for various domains\, including low-level computer vision and neural fields. We will start by discussing the latest Lookup Table (LUT)-based approach for Single-Image Super-Resolution (SISR). Our proposed Hundred-Kilobyte LUT (HKLUT) requires only 100KB\, 10X less than the second smallest LUT-based method\, and delivers superior performance. Moreover\, we will explore the field of Implicit Neural Representation (INR)\, where inference efficiency is often overlooked. We propose the Activation-Sharing Multi-Resolution (ASMR) coordinate network to enhance INR’s rendering efficiency. By sharing activations across data grids\, ASMR can reduce its Multiply-Accumulate (MAC) operations by up to 500x and improve reconstruction quality. \nSpeaker\nMr. Jason Chun Lok LI\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nBiography of the speaker\nMr. Jason Chun Lok LI holds a BEng degree from the Department of Electrical and Electronic Engineering at The University of Hong Kong\, obtained in 2020. He is currently continuing his studies at the same institution\, working towards a PhD. His research interest lies in the development of domain-specific techniques for efficient deep learning on edge devices. \nOrganizer\nProf. Ngai WONG \nAll are welcome.
URL:https://ece.hku.hk/events/20240516-1/
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:20240516T143000
DTEND;TZID=Asia/Hong_Kong:20240516T153000
DTSTAMP:20260513T031747
CREATED:20240507T082448Z
LAST-MODIFIED:20250114T063241Z
UID:18500-1715869800-1715873400@ece.hku.hk
SUMMARY:RPG Seminar – Exploration of Novel Operators with Memristor Arrays Towards Efficient and Robust In-memory Computing
DESCRIPTION:Abstract\nThe past decade of escalated development in deep learning (DL) has achieved unprecedented success in engineering fields. In particular\, deep neural networks (DNNs) via deep learning have achieved remarkable success across various applications. However\, challenges remain in the hardware implementation of these software-oriented AI algorithms\, primarily due to the reliance on traditional von Neumann computing architectures which are inefficient and lead to high power usage and latency particularly at the edge computing level. To address these issues\, compute-in-memory (CIM) using non-volatile memristive devices presents a promising solution. CIM leverages in-memory data processing to reduce data movement\, thereby improving efficiency. Therefore\, a core issue in artificial intelligence-related fields lies in leveraging hardware practice experience to explore and develop neuron models and operational operators. In the upcoming talk\, an innovative memristive unit cell based on the arithmetic unit model will be introduced\, aiming to explore its performance and robustness in emerging operational networks within AI fields. \nSpeaker\nMr. Yuan REN\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nBiography of the speaker\nMr. Yuan REN received the M.S. degree in electrical and computer engineering from the University of Macau (UM)\, Macao. He then joined the SoC Key Laboratory\, Peking University Shenzhen Institute and PKU-HKUST Shenzhen-Hong Kong Institution\, Guangdong\, China. He is currently pursuing the Ph.D. degree in electrical and electronic engineering from the University of Hong Kong (HKU)\, under the supervision of Dr. Ngai Wong. His research focuses on algorithm-hardware co-design for AI accelerator and memristor-based compute-in-memory integrated circuits. \nOrganizer\nProf. Ngai WONG \nAll are welcome.
URL:https://ece.hku.hk/events/20240516-2/
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:20240517T100000
DTEND;TZID=Asia/Hong_Kong:20240517T110000
DTSTAMP:20260513T031747
CREATED:20240510T012737Z
LAST-MODIFIED:20250114T063205Z
UID:18502-1715940000-1715943600@ece.hku.hk
SUMMARY:RPG Seminar – Manipulating Light Scattering at the Nanoscale by Metasurface
DESCRIPTION:Abstract\nLight scattering is a fundamental optical process that accounts for many optical phenomena and applications. This process comes from the interaction between light and scattering particles\, or scatters. It greatly depends on parameters such as the scatters’ shapes and refractive index\, the polarization and wavelength of light. We will show that by arranging the specially designed nano scatters on a flat surface to form a metasurface\, the output light field can be manipulated at the nanoscale\, which will lead to many promising applications. \nTwo main topics will be discussed in this seminar. The first topic relates to tri-channel metalenses. Since it is difficult to encode three independent phase information at single-pixel or single-cell level\, most current designs use spatial multiplexing strategies including segmentation\, interleaving and multilayer integration\, which would result in large unit pixel sizes and limited performances. In this seminar\, we will present a single-celled design method to achieve tri-functional metalenses. Another topic relates to broadband antireflection by metasurfaces. We have proposed a quasi-random design method\, and developed a high-throughput nanofabrication method to fabricate the metasurfaces. \nSpeaker\nMr. Xudong GUO\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nBiography of the speaker\nMr. Xudong GUO received the B.Eng. degree in Optoelectronic Information Science and Engineering from Changchun University of Science and Technology\, Changchun\, in 2018. He is currently working toward the Ph.D. degree in electrical and electronic engineering with the Department of Electrical and Electronic Engineering\, The University of Hong Kong\, Hong Kong. His research interests include metasurface\, holography and imaging. \nOrganizer\nProf. Kenneth K. Y. WONG
URL:https://ece.hku.hk/events/20240517-2/
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:20240517T110000
DTEND;TZID=Asia/Hong_Kong:20240517T120000
DTSTAMP:20260513T031747
CREATED:20240510T040913Z
LAST-MODIFIED:20250114T063123Z
UID:18504-1715943600-1715947200@ece.hku.hk
SUMMARY:RPG Seminar – Scalable Optical Neural Network Based on Parametric Process
DESCRIPTION:Abstract\nIn the past decades\, with the rapidly increasing data\, AI technology\, including neural network (NN) shows more and more powerful ability. However\, the development of electronic hardware meets a dilemma because of the physical limitation\, which restricts the computation performance growth of NN. Thus\, developing the next-generation computation platform for NN is necessary. Since the optical system can also provide the solution to carry and process the information\, optical neural network (ONN) is developed\, and it shows high energy efficiency\, low crosstalk\, low latency\, and massive parallelism computation. Most ONNs are realized by direct spatial manipulation and observation with digital micromirror device\, spatial light modulator\, and camera. But those items can only provide a frame rate of several kHz\, which will limit the computation speed of ONN. \nThanks to the development of high-speed optical communication system\, superior optical manipulation and observation methods are available. The mode-locked laser can achieve ultrawide bandwidth for spectral encoding. By achieving wavelength-to-time mapping with temporal dispersion\, time-stretch method or we also called it as dispersive Fourier transform can be utilized for high-frame rate spectrum observation\, which is widely applied in microscopy\, and soliton dynamics observation. Here\, we applied to our ONN to achieve high computation frame rate. \nSpeaker\nMr. Xin DONG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nBiography of the speaker\nMr. Xin DONG 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 worked as a Research Scientist with the Wuhan National Laboratory for Optoelectronics\, and School of Optical and Electronic Information\, HUST from 2019 to 2020. He is currently a Ph.D. Candidate at the Department of Electrical and Electronic Engineering\, University of Hong Kong\, Hong Kong\, China. His research interests include fiber nonlinearities\, ultrafast spectroscopy\, fluorescence imaging\, structure illumination and optical neural network. \nOrganizer\nProf. Kenneth K. Y. WONG \nAll are welcome.
URL:https://ece.hku.hk/events/20240517-4/
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:20240517T140000
DTEND;TZID=Asia/Hong_Kong:20240517T150000
DTSTAMP:20260513T031747
CREATED:20240510T013911Z
LAST-MODIFIED:20250114T063038Z
UID:18503-1715954400-1715958000@ece.hku.hk
SUMMARY:RPG Seminar – Trajectory Inference of T-Cell Activation from Label-free Single-cell Biophysical Morphologies with StaVia
DESCRIPTION:Abstract:\nBlood analysis is an indispensable clinical tool for human health and diseases. Specifically\, the overarching challenge in characterization of blood\, notably immune cells\, is to identify the cellular phenotypes at the single-cell precision to dissect the complex functional roles of different cell types/states. Strategies for phenotyping immune cells enable biological discovery and shed light on the immune system’s intricate mechanisms and the enormous heterogeneity of hematopoiesis. They are instrumental in the quality assessment and control of emerging immunotherapy methods. \nOften overlooked are the biophysical properties of the immune cell\, which simultaneously impact and are affected by its molecular signature. Defining biophysical markers\, which are label-free in nature\, could overcome the issues of scale and cost of analyzing numerous single cells. However\, deep biophysical profiling of single-cell requires both high-throughput and high-content that are not achievable or affordable with current technologies. Here we present a single-cell image-based trajectory inference strategy for tracking human T-cell activation based on the label-free biophysical morphology of T-cells. \nWe used our recently developed ultra-large-scale label-free imaging technology (up to 100\,000 cells/sec)\, multi-ATOM\, to extract high-resolution quantitative morphological and biophysical features (e.g. cell size\, shape\, dry mass density\, subcellular distributions) from the single-cell images. This is integrated with our unsupervised trajectory inference method StaVia to parameterize the morphology of each T-cell into a high-dimensional feature profile (> 90 dimensions) in order to uncover cellular dynamics of the underlying T-cell activation. We demonstrate that the integration of StaVia with multi-ATOM-derived single cells biophysical profiles reveal not only the overall T-cell activation process but also the subtle distinct morphological changes of CD4+ and CD8+ T-cells activations. We anticipate this work could spearhead further research in employing single-cell biophysical phenotypes as effective surrogate biomarkers of immune cell profiling in health and disease. Ultimately\, it could potentially inspire new cost-effective clinical diagnostic strategies in monitoring various immune-related disease/treatment progression. \nSpeaker\nMr. Kobashi MINATO\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nBiography of the speaker\nMr. Kobashi MINATO received his BEng degree in biological Engineering at The Hong Kong University of Science and Technology in 2022. He is currently a MPhil student supervised by Prof. Kevin K.M. Tsia in the department of electrical and electronic engineering. His research interest resides in the field of biomedical engineering and focusing on the analysis of biological data. \nOrganizer\nProf. Kevin K.M. TSIA\n \nAll are welcome.
URL:https://ece.hku.hk/events/20240517-3/
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:20240517T150000
DTEND;TZID=Asia/Hong_Kong:20240517T160000
DTSTAMP:20260513T031747
CREATED:20240418T012121Z
LAST-MODIFIED:20250114T062952Z
UID:18278-1715958000-1715961600@ece.hku.hk
SUMMARY:RPG Seminar – A Multi-Agent and Self-Adaptive Framework for Portfolio Management in Computational Finance
DESCRIPTION:Abstract:\nFinancial portfolio management (PM) is a very important topic in computational finance\, with its primary objective of achieving higher returns while reducing investment risks through dynamically allocating capital to different assets in a portfolio. Recently\, deep or reinforcement learning(DL/RL)-based PM approaches have been applied to capture the valuable opportunities from the underlying financial market yet the trade-off between returns and risks is definitely a great challenge. Accordingly\, this talk will consider the newly proposed Multi-Agent and Self-Adaptive (MASA) framework to dynamically balance the long-term portfolio profits and potential short-term risks. Through the close cooperation between the RL-based agent and solver-based agent\, the MASA framework continuously learns the profitable patterns of stock data from the concerned financial market\, monitors the current trends of financial markets\, and carefully evaluates the future risk exposures such that the newly balanced investment portfolios can adapt to the highly turbulent trading environments. Furthermore\, due to the high flexibility of the MASA framework\, its agent can be adaptively adjusted to satisfy a diversity of trading constraints and investor preferences. The reported results demonstrate the great potential of the proposed framework on PM tasks in various financial markets. Beyond the DL/RL-based PM approaches\, this talk will also introduce two novel meta-heuristic algorithms for solving continuous optimization problems with complex natures. The case studies show the significant advantages of the proposed algorithms on optimizing large-scale financial portfolios in such ever-changing financial markets. Most importantly\, the proposed frameworks shed light on many possible applications in computation finance like pair trading\, orderbook trading\, multi-factor model optimization\, etc. \nSpeaker: Mr. Zhenglong LI\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nBiography of the speaker:\nMr. Zhenglong LI received the B.Eng. degree in Electronic Information Science and Technology and B.Econ. degree in Financial Engineering both from Jinan University\, and the M.S. degree in Electrical and Electronics Engineering from the University of Hong Kong. He is currently pursuing the Ph.D degree with the Department of Electrical and Electronic Engineering at the University of Hong Kong\, under the supervision of Dr. Vincent Tam and Prof. Lawrence Yeung. His research interest lies in computational finance including portfolio optimization\, risk management\, pair trading\, and financial sentiment analysis. \nOrganizer:\nDr. Vincent TAM
URL:https://ece.hku.hk/events/20240517-1/
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:20240520T140000
DTEND;TZID=Asia/Hong_Kong:20240520T150000
DTSTAMP:20260513T031747
CREATED:20240514T081548Z
LAST-MODIFIED:20250114T062839Z
UID:18512-1716213600-1716217200@ece.hku.hk
SUMMARY:EEE MasterClass (EEE 大師講堂) - Mixed-Dimensional Heterostructures for Electronic and Energy Technologies
DESCRIPTION:Abstract\nLayered two-dimensional (2D) materials interact primarily via van der Waals bonding\, which has created new opportunities for heterostructures that are not constrained by epitaxial lattice matching requirements. However\, since any passivated\, dangling bond-free surface interacts with another via non-covalent forces\, van der Waals heterostructures are not limited to 2D materials alone. In particular\, 2D materials can be integrated with a diverse range of other materials\, including those of different dimensionality\, to form mixed-dimensional van der Waals heterostructures. Furthermore\, chemical functionalization provides additional opportunities for tailoring the properties of 2D materials and the degree of coupling across heterointerfaces. In this manner\, a variety of optoelectronic and energy applications can be enhanced including photodetectors\, optical emitters\, supercapacitors\, and batteries. Furthermore\, mixed-dimensional heterostructures enable unprecedented electronic device function to be realized including neuromorphic memtransistors\, mixed-kernel heterojunction transistors\, and moiré synaptic transistors. In addition to technological implications for electronic and energy technologies\, this talk will explore several fundamental issues including band alignment\, doping\, trap states\, and charge/energy transfer across mixed-dimensional heterointerfaces. \nSpeaker\nProf. Mark C. HERSAM\nWalter P. Murphy Professor\,\nMaterials Science and Engineering\,\nNorthwestern University \nBiography of the Speaker\nProf. Mark C. HERSAM is the Walter P. Murphy Professor of Materials Science and Engineering\, Director of the Materials Research Center\, and Chair of the Materials Science and Engineering Department at Northwestern University. He also holds faculty appointments in the Departments of Chemistry\, Applied Physics\, Medicine\, and Electrical Engineering. He earned a B.S. in Electrical Engineering from the University of Illinois at Urbana-Champaign (UIUC) in 1996\, M.Phil. in Physics from the University of Cambridge (UK) in 1997\, and Ph.D. in Electrical Engineering from UIUC in 2000. His research interests include nanomaterials\, additive manufacturing\, nanoelectronics\, scanning probe microscopy\, renewable energy\, and quantum information science. Dr. Hersam has received several honors including the Presidential Early Career Award for Scientists and Engineers\, TMS Robert Lansing Hardy Award\, MRS Mid-Career Researcher Award\, AVS Medard Welch Award\, U.S. Science Envoy\, MacArthur Fellowship\, and eight Teacher of the Year Awards. Dr. Hersam has been repeatedly named a Clarivate Analytics Highly Cited Researcher with over 700 peer-reviewed publications that have been cited more than 70\,000 times with an h-index of 128. An elected member of the American Academy of Arts and Sciences\, National Academy of Engineering\, and National Academy of Inventors with over 170 issued and pending patents\, Dr. Hersam has founded two companies\, NanoIntegris and Volexion\, which are suppliers of nanoelectronic and battery materials\, respectively. Dr. Hersam is a Fellow of MRS\, ACS\, AVS\, APS\, AAAS\, SPIE\, and IEEE\, and also serves as an Executive Editor of ACS Nano. \nOrganizer\nProf. Han WANG \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240520-1/
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:20240521T160000
DTEND;TZID=Asia/Hong_Kong:20240521T170000
DTSTAMP:20260513T031747
CREATED:20240514T041838Z
LAST-MODIFIED:20250114T062744Z
UID:18510-1716307200-1716310800@ece.hku.hk
SUMMARY:Energy Intelligent Computing Devices Based on 2D Materials
DESCRIPTION:Abstract\nDespite the long and crucial role of traditional solid-state physics for current silicon-based technologies\, next-generation neuromorphic\, non-volatile memory\, and energy devices that are key components in the era of the Internet of Things (IoT) require novel working principles with quantum physics emerging in low-dimensional materials. The main research direction for future devices is to realize ‘ultralow device operation energy’\, ‘ultrahigh device operation speed’\, and ‘large-scale device integration (up to 10)’\, which calls for exploring diverse quantum phenomena in low dimensional device components. In this talk\, I will present some of our recent efforts to establish new device physics for energy-intelligent devices\, which could be a milestone for promising future devices. In particular\, dynamic convolution neural network\, phase transition and other intriguing quantum physics in two-dimensional (2D) materials will be discussed along with logic device\, neuromorphic computing\, and energy device applications. \nSpeaker\nProf. Heejun YANG\nQuantum Energy Device (QED) Lab\nDepartment of Physics\,\nKorea Advanced Institute of Science and Technology (KAIST) \nBiography of the Speaker\nProf. Heejun YANG received B.S. in physics from KAIST in 2003 and a joint Ph.D. in physics from Seoul National University (Korea) and University Paris-Sud XI (France) in 2010. He was awarded the IUPAP Young Scientist Prize (YSP) in Semiconductor Physics 2018 for his outstanding contribution to novel interface devices based on structural\, electronic\, and quantum-state control with van der Waals layered materials. His Ph.D. subject was on graphene by scanning tunnelling microscopy and spectroscopy (STM/STS)\, and he experienced industrial device studies in Samsung Electronics from 2010 to 2012. Then\, he conducted his research on graphene spintronics in Albert Fert’s (2007 Novel laureate) group in CNRS/Thales as a postdoc from 2012 to 2014. Based on his research background on molecular and nanometer-scale studies (in Seoul and Paris) and electric and spintronic device physics (in Samsung and CNRS/Thales)\, he moved to Sungkyunkwan University (2014~2021) and KAIST (2021~) and started original device studies with phase engineering of low-dimensional materials. He has proposed novel and conceptual interface devices such as ‘Graphene Barristor’ and ‘Ohmic homojunction contact between semiconductor channel and metal electrodes’. In 2022\, he gave an invited talk at the IUPAP centenary symposium as a representative YSP winner. \nOrganizer\nProf. C.L. TAN \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240521-1/
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:20240522T100000
DTEND;TZID=Asia/Hong_Kong:20240522T110000
DTSTAMP:20260513T031747
CREATED:20240520T042136Z
LAST-MODIFIED:20250114T062646Z
UID:18567-1716372000-1716375600@ece.hku.hk
SUMMARY:Optimization of Phase Change Memory for In-Memory Computing and Packaging for Small Computers
DESCRIPTION:Abstract\nThe need to shuttle data between processing and memory units has been a key performance bottleneck for conventional hardware implementations of artificial neural networks. Analog in-memory computing (AIMC) emerges as a promising solution to this challenge by directly performing computations within non-volatile memory devices\, such as phase change memory (PCM). However\, the utilization of PCMs for analog computing introduces nonidealities\, including resistance drift\, read noise\, limited memory window\, and various device failures. I will discuss our work on optimizing PCM devices to alleviate these nonidealities and mitigate their impact on AIMC. Additionally\, I will talk about the effort to packaging such computer chips with photovoltaic power conversion devices and optical communication devices for ultra-small form factor edge computing applications. \nSpeaker\nProf. Ning LI\nAssociate professor\,\nDepartment and the Material Research Institute\,\nPenn State University \nBiography of the Speaker\nProf. Ning LI obtained his B.S. and M.S. from Tsinghua University and his Ph.D. from the University of Texas at Austin\, TX. He was a Research Staff Member at IBM T. J. Watson Research Center\, Yorktown Heights\, NY\, from 2010 to 2022. His research work is related to memory devices and their applications in neuromorphic computing\, flexible and new form factor devices and systems\, optoelectronic devices for interconnects and communications\, heterogeneous integration\, organic electronics\, etc. He published ~100 research papers in scientific journals and peer reviewed conferences\, including Nature Photonics\, Nature Communications\, Advanced Materials\, IEDM\, VLSI\, OFC\, etc. He was awarded more than 250 US patents\, many IBM High Value Patent Awards\, IBM Invention Achievement Awards\, and Master Inventor Awards. His work has been featured on Nature Research Highlight\, Semiconductor Today\, etc.  He joined the Electrical Engineering Department and the Material Research Institute at Penn State University as an associate professor in 2024. \nOrganizer: Prof. Han WANG \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240522-1/
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/2024/05/1280-6.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240523T143000
DTEND;TZID=Asia/Hong_Kong:20240523T180000
DTSTAMP:20260513T031747
CREATED:20240513T012814Z
LAST-MODIFIED:20250114T062539Z
UID:18505-1716474600-1716487200@ece.hku.hk
SUMMARY:Workshop on Frontiers of Legged Robotics 2024
DESCRIPTION:The Faculty of Engineering\, The University of Hong Kong is organizing the “Workshop on Frontiers of Legged Robotics 2024”. The workshop will be held on May 23\, 2024 (Thursday) from 2:30 pm to 6:00 pm at Lecture Theatre A\, G/F\, Chow Yei Ching Building\, HKU. \nKeynote Speaker for William Mong Distinguished Lecture:\n– Prof Abderrahmane Kheddar\, The French National Centre for Scientific Research (CNRS) \nSpeakers*: \n– Prof Hua Chen\, Zhejiang University and LimX Dynamics – Dr Zhicheng He\, Leju (Shenzhen) Robotics Co.\, Ltd – Dr Baiyu Pan\, UBTech Co.\, Ltd – Prof Peng Lu\, Department of Mechanical Engineering\, The University of Hong Kong – Prof Jiangcheng Chen\, Department of Industrial and Manufacturing Systems Engineering\, The University of Hong Kong \nRegister now: https://hkuems1.hku.hk/hkuems/ec_hdetail.aspx?guest=Y&ueid=93930 \nFor more details\, please visit: https://sites.google.com/view/workshop-legged-robotics \n*Speakers are in alphabetical order by surname.
URL:https://ece.hku.hk/events/20240523-1/
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/2024/05/787584.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240524T150000
DTEND;TZID=Asia/Hong_Kong:20240524T163000
DTSTAMP:20260513T031747
CREATED:20240517T043054Z
LAST-MODIFIED:20250114T044042Z
UID:18564-1716562800-1716568200@ece.hku.hk
SUMMARY:EEE MasterClass (EEE 大師講堂) – Research Advances in Energy Storage Systems
DESCRIPTION:Abstract\nAs the penetration of variable renewable generation increases in power systems\, issues such as grid stiffness\, larger frequency deviations\, and grid stability are becoming more relevant. In this context\, Energy Storage Systems (ESSs) are proving to be effective in facilitating the integration of renewable resources\, and thus are being widely deployed in both microgrids and large power grids.  This talk will review several energy storage technologies\, particularly Compress Air Energy Storage (CAES)\, flywheels\, batteries\, and thermal energy systems\, and their modelling and applications for power systems.  An overview will be provided of the work being carried out by Prof. Canizares’ group at the University of Waterloo on all these energy storage systems\, focusing on novel models and applications in microgrids and distribution and transmission grids for system stability and control\, in particular for frequency regulation. \nSpeaker\nProf. Claudio Cañizares\nProfessor and Hydro One Endowed Chair\,\nElectrical and Computer Engineering (ECE) Department\,\nUniversity of Waterloo \nBiography of the Speaker\nProf. Claudio Cañizares is a University Professor and Hydro One Endowed Chair in the electrical and computer engineering (ECE) department at the University of Waterloo\, where he has held various academic and administrative positions since 1993. In 2021\, he was appointed the Executive Director of the Waterloo Institute for Sustainable Energy (WISE). He received an electrical engineering degree from the Escuela Politécnica Nacional (EPN) in Quito\, Ecuador in 1984\, where he held different academic and administrative positions between 1983 and 1993\, and his MSc (1988) and PhD (1991) degrees in electrical engineering from the University of Wisconsin-Madison\, in the USA. His research activities focus on the study of stability\, control\, optimization\, modelling\, simulation\, and computational issues in bulk power systems\, microgrids\, and energy systems in the context of competitive energy markets and smart grids. Professor Cañizares has collaborated with multiple industry and university researchers in Canada and abroad and supervised/co-supervised nearly 180 research fellows and students. He has authored/co-authored more than 370 publications with over 29\,000 citations and a 77 H index in Google Scholar and has been invited to deliver over 225 keynote speeches\, seminars\, tutorials\, and presentations at numerous institutions and conferences worldwide. He is the current Editor-In-Chief of the IEEE Transactions on Smart Grid\, a Fellow of the Institute of Electrical & Electronic Engineering (IEEE)\, a Fellow of the Royal Society of Canada\, and a Fellow of the Canadian Academy of Engineering. He is the recipient of the 2017 IEEE Power & Energy Society (PES) Outstanding Power Engineering Educator Award\, the 2016 IEEE Canada Electric Power Medal\, and multiple IEEE PES Technical Council and Committee awards and recognitions\, holding leadership positions in several IEEE-PES Committees\, Working Groups\, and Task Forces. In 2021 and 2022\, he received the Award for Excellence in Graduate Supervision from the University of Waterloo. \nOrganizer: Prof. Y. WANG \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240524-1/
LOCATION:Room CPD-3.01\, 3/F\, Run Run Shaw Tower\, The University of Hong Kong
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240531T110000
DTEND;TZID=Asia/Hong_Kong:20240531T120000
DTSTAMP:20260513T031747
CREATED:20240506T014649Z
LAST-MODIFIED:20250114T043911Z
UID:18494-1717153200-1717156800@ece.hku.hk
SUMMARY:Localization of a Non-Cooperative Object Irrespective of the Range to Receivers
DESCRIPTION:Abstract\nPosition-related services and applications appear everywhere in our daily lives and precise positioning is indispensable.  For non-cooperative localization of an object by time difference of arrival (TDOA) such as in an integrated sensing and communications (ISAC) environment\, it requires the knowledge that the object is near to or far from the receivers.  If the object is close\, a near-field model is used to determine the unique coordinates of the object.  If it is distant\, a far-field model needs to be applied instead to obtain its direction.  Such knowledge\, however\, is seldom available in practice. This talk introduces a novel representation of the object position\, called the modified polar representation (MPR)\, which can eliminate the necessity of such knowledge.  MPR leads to a unified model that naturally yields the unique coordinates of the object if it is near and the direction if it is far.  Both the theory by the Cramer-Rao Lower Bound (CRLB) and the Hybrid Bhattacharyya-Barankin (HBB) Bound\, and the simulations by the Maximum Likelihood Estimator (MLE) support the effectiveness of MPR for TDOA localization. \nSpeaker:\nDr. Dominic K. C. HO\nProfessor\, University of Missouri\, USA \nBiography of the Speaker\nDr. Dominic K. C. HO was born in Hong Kong.  He received the BSc degree with First Class Honors and the PhD degree in Electronic Engineering\, both from the Chinese University of Hong Kong.  He was a research associate at the Royal Military College of Canada\, a member of scientific staff at the Bell-Northern Research\, and a faculty at the University of Saskatchewan\, Canada.  Since 1997\, he has been with the University of Missouri\, where he is a professor in the Electrical Engineering and Computer Science Department.  His research interests are in sensor array processing\, source localization\, subsurface object detection\, and wireless communications.  He has been active in the International Telecommunications Union (ITU) standard developments between 1995 and 2012.  He was the rapporteur of one recommendation and the editor of several others.  He was an Associate Editor of the IEEE Transactions of Signal Processing (2003-2006\, 2009-2013) and the IEEE Signal Processing Letters (2004-2008).  He served as the Chair of the IEEE Sensor Array Multichannel (SAM) Technical Committee from 2013 to 2014 and the Past Chair in 2015.  He was Technical Co-Chair of the IEEE International Conference on Acoustics\, Speech and Signal Processing (ICASSP) held in Shanghai\, in 2016.  He is an inventor of 22 patents in the United States\, Canada\, Europe and Asia on geolocation and signal processing for wireless communications.  He is a fellow of the IEEE. \nOrganizer\nProf. Y.C. WU \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240531-1/
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/2024/05/1280-4.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240531T140000
DTEND;TZID=Asia/Hong_Kong:20240531T170000
DTSTAMP:20260513T031747
CREATED:20240521T083633Z
LAST-MODIFIED:20250114T043839Z
UID:18570-1717164000-1717174800@ece.hku.hk
SUMMARY:Real-time Twisting on a Chip
DESCRIPTION:Meeting ID: 939 1846 8563 \nAbstract\nOptical nanostructures and two-dimensional materials (2DM) have optical properties that are widely tunable via several approaches\, such as heating\, electrostatic gating\, and interfacial engineering such as twisting. Being able to tailor the interfacial properties in a similar real-time manner represents the next leap in our ability to modulate the underlying physics and build exotic photonics devices. We demonstrate the first on-chip platform designed for optical nanostructures and 2D materials with in situ tunable interfacial properties\, utilizing a microelectromechanical system (MEMS). Each of these compact\, cost-effective\, and versatile devices is a standalone micromachine that allows voltage-controlled approaching\, twisting\, and pressurizing of two sheets of materials with high accuracy. \nSpeaker\nDr. Haoning TANG\nHarvard Quantum Initiative Postdoctoral Fellow\,\nJohn A. Paulson School of Engineering Applied Science\,\nHarvard University \nBiography of the Speaker\nDr. Haoning TANG is the Harvard Quantum Initiative Postdoctoral Fellow at John A. Paulson School of Engineering Applied Science at Harvard University. She obtained bachelor’s degree at The Hong Kong University of Science and Technology\, and Ph.D. at Harvard. Her primary research interest is in the nonlinear and quantum optical properties of metamaterials and low-dimensional materials\, and the engineering of these properties through advanced nanotechnologies including micro-electricalmechanical systems (MEMS). \nOrganizer\nProf. Kaibin HUANG \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240531-2/
LOCATION:Online via Zoom
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240531T150000
DTEND;TZID=Asia/Hong_Kong:20240531T160000
DTSTAMP:20260513T031747
CREATED:20240521T090117Z
LAST-MODIFIED:20250114T043757Z
UID:18572-1717167600-1717171200@ece.hku.hk
SUMMARY:Integrated Nonlinear Multimode Photonics for Information Processing and Computation
DESCRIPTION:Meeting ID:937 8072 8049\n \nAbstract\nPhotonics technology has become indispensable in communication\, imaging\, sensing\, metrology\, and more recently\, in signal processing and computation. These advancements are made possible through optical systems that leverage the control of multiple degrees of freedom of light\, e.g.\, in space/momentum\, time/frequency\, angle/orbital angular momentum and polarization. Recently\, the integration of table-top optical systems into photonic integrated circuits has not only miniaturized the form factor but also enhanced light-matter interaction. This offers enormous opportunities to explore fundamental nonlinear optical physics and unlock new functionalities in integrated photonics. \nThe first part of my talk focuses on the fundamental aspects of integrated nonlinear photonics. I will show how we optically induce the second-order ((2)) nonlinearity in silicon nitride photonics\, along with techniques to achieve quasi-phase-matching for the second-harmonic generation process. Moreover\, I will discuss the generalization of our approach to other (2) nonlinear processes\, such as sum-frequency generation\, backward second-harmonic generation\, and combined (2) and Kerr nonlinear effects for different participating spatial modes. \nThe second part of my talk is on the applications of integrated nonlinear multimode photonics for information processing and computing. I will discuss the use of integrated Kerr microcombs for microwave photonics\, showcasing the reconfigurable microwave filtering based on inherently rich soliton states from silicon nitride microresonators. I will also show how we combine second-harmonic generation and multiple light scattering in disordered lithium niobite (2) nanocrystals for various machine learning applications. Additionally\, I will introduce a new reservoir computing paradigm harnessing the massive spatial parallelism of light. \nSpeaker\nDr. Jianqi HU\nPostdoc Researcher\,\nÉcole Polytechnique Fédérale de Lausanne (EPFL)\, Switzerland \nBiography of the Speaker\nDr. Jianqi HU is currently a postdoc researcher in Prof. Tobias Kippenberg’s group at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. He received the B.E. from the University of Electronic Science and Technology of China in 2016\, and the Ph.D. in photonics from EPFL in 2021\, advised by Prof. Camille Brès. After completing the Ph.D.\, he continued his research as a postdoc at EPFL from 2021 to 2022\, and then he was an SNF postdoc fellow at Ecole Normale Supérieure\, France\, working with Prof. Sylvain Gigan from 2022 to 2023. His research interests include integrated nonlinear photonics\, frequency microcombs\, structured light\, and photonic computing. \nOrganizer\nProf. Kaibin HUANG \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240531-3/
LOCATION:Online via Zoom
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240603T110000
DTEND;TZID=Asia/Hong_Kong:20240603T120000
DTSTAMP:20260513T031747
CREATED:20240529T013654Z
LAST-MODIFIED:20250114T043655Z
UID:18654-1717412400-1717416000@ece.hku.hk
SUMMARY:Extreme Spatial Multiplexing: A Fluid Antenna System Approach
DESCRIPTION:Abstract\nFluid antenna system (FAS) represents shape-flexible position-flexible antenna technologies for wireless communications and has recently emerged as a new degree of freedom for wireless communication design and optimization. The unique feature of FAS also changes the way in which interference is mitigated. In this talk\, we will first take a closer look at massive multiuser MIMO (multiple-input multiple-output) and discuss why massive MIMO alone cannot be a feasible solution for extreme spatial multiplexing of an enormous number of users. We then present how FAS at each user can reduce the burden of the base station and enable massive MIMO to handle a huge number of users with little channel state information (CSI) at the base station. The results reveal that 1000 of users can be served on the same physical data channel if massive MIMO combines with FAS. The talk will be concluded by sharing some recent updates on the implementation of FAS. \nSpeaker\nProf. Kai-Kit WONG\nProfessor of Wireless Communications\,\nUniversity College London \nBiography of the Speaker\nProf. Kai-Kit WONG received the BEng\, the MPhil\, and the PhD degrees\, all in Electrical and Electronic Engineering\, from the Hong Kong University of Science and Technology\, Hong Kong\, in 1996\, 1998\, and 2001\, respectively. He is Chair Professor of Wireless Communications at the Department of Electronic and Electrical Engineering\, University College London. His current research centers around 6G mobile communications. He is one of the early researchers who proposed multiuser MIMO. His first paper on multiuser MIMO was published in WCNC 2000 which appeared to be the first ever research paper on this topic. He is Fellow of IEEE and IET. He served as the Editor-in-Chief for IEEE Wireless Communications Letters between 2020 and 2023. \nOrganizer\nProf. Y.C. WU \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240603-1/
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:20240606T153000
DTEND;TZID=Asia/Hong_Kong:20240606T163000
DTSTAMP:20260513T031747
CREATED:20240603T015835Z
LAST-MODIFIED:20250114T043621Z
UID:18751-1717687800-1717691400@ece.hku.hk
SUMMARY:Stabilizing Control Interactions of Converter-Based Resources
DESCRIPTION:Abstract\nThe widespread use of power electronic converters in renewable energy resources and flexible ac or dc transmission systems is profoundly changing dynamics and control of power systems. These converter-based resources are significantly different from synchronous generators in respect to their physical properties and control dynamics. The differences pose challenges to the stability and power quality of electricity supply. This lecture will give an overview of instability issues caused by dynamic interactions of converter-based resources\, and then discuss dynamics analysis and control methods for addressing the problems. Emerging trends and challenges with grid integration of converter-based resources will also be covered. \nSpeaker\nProf. Xiongfei WANG\nProfessor\,\nKTH Royal Institute of Technology\,\nStockholm\, Sweden \nBiography of the Speaker\nProf. Xiongfei WANG is currently a full-time Professor at the Department of Electrical Engineering\, KTH Royal Institute of Technology\, Stockholm\, Sweden\, a part-time Professor at Aalborg University\, Aalborg\, Denmark\, and a Visiting Professor at Hitachi Energy Research Center\, Vasteras\, Sweden. His research interests include modeling and control of power electronic converters\, stability and power quality of power-electronic-dominated power systems\, and high-power converters. He is an IEEE Fellow and the Executive Editor (Editor-in-Chief) for the IEEE Transactions on Power Electronics Letters\, as well as an Associate Editor for the IEEE Journal of Emerging and Selected Topics in Power Electronics. He received 10 IEEE Prize Paper Awards\, the 2016 AAU Talent for Future Research Leaders\, the 2018 Richard M. Bass Outstanding Young Power Electronics Engineer Award\, the 2019 IEEE PELS Sustainable Energy Systems Technical Achievement Award\, and the 2022 Isao Takahashi Power Electronics Award. \nOrganizer\nProf. Ron S.Y. HUI & Prof. S.C. TAN \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240606-1/
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/2024/06/1280-4.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240611T100000
DTEND;TZID=Asia/Hong_Kong:20240611T150000
DTSTAMP:20260513T031747
CREATED:20240606T032557Z
LAST-MODIFIED:20250114T043541Z
UID:18779-1718100000-1718118000@ece.hku.hk
SUMMARY:Workshop on Optical and Computational Technologies to Combat Microplastics and Nanoplastics Pollution
DESCRIPTION:Organizer\nImaging Systems Laboratory\, Department of Electrical and Electronic Engineering\, The University of Hong Kong \nPartners \n\nDepartment of Food Science and Nutrition\, The Hong Kong Polytechnic University\nSchool of Energy and Environment\, City University of Hong Kong\nDepartment of Chemistry\, City University of Hong Kong\nDepartment of Science and Environmental Studies (SES)\, The Education University of Hong Kong\nHong Kong Marine Ecological Association\nEnvironmental Protection Department/HKSAR Government\n\nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240611-1/
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/2024/06/2212323.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240617T143000
DTEND;TZID=Asia/Hong_Kong:20240617T153000
DTSTAMP:20260513T031747
CREATED:20240603T025204Z
LAST-MODIFIED:20250114T043355Z
UID:18754-1718634600-1718638200@ece.hku.hk
SUMMARY:Open-Source Ultra-Low Power Edge AI Systems for a Connected World
DESCRIPTION:Abstract\nEdge computing is becoming an essential concept covering multiple domains nowadays as our world becomes increasingly connected to enable the Internet of Things (IoT) concept. In addition\, the new wave of Artificial Intelligence (AI)\, particularly complex Machine Learning (ML) and Deep Learning (DL) models\, is demanding new computing paradigms beyond traditional general-purpose computing to make IoT a viable reality in a sustainable world. In this seminar\, Prof. Atienza will discuss new approaches to effectively design the next generation of ultra-low power edge AI computing architectures by taking inspiration from how biological computing systems operate. In particular\, these novel bioinspired edge AI architectures include two key concepts. First\, it exploits the idea of accepting computing inexactness and integrating multiple computing acceleration engines and low-power principles to create a new open-source eXtended and Heterogeneous Energy-Efficient hardware Platform (called x-HEEP). Second\, x-HEEP can be instantiated for different application domains of edge AI to operate ensembles of neural networks and federated learning to improve the ML/DL outputs’ robustness at system level\, while minimizing memory and computation resources for the target application. Overall\, x-HEEP instantiations for edge AI applications included in-memory computing or run-time reconfigurable coarse-grained accelerators to minimize energy according to the required precision of the target application. \nSpeaker\nProf. David ATIENZA\nProfessor\,\nHead of the Embedded Systems Laboratory (ESL)\,\nScientific Director of the EcoCloud Sustainable Computing Center\,\nEPFL\, Switzerland \nBiography of the Speaker\nProf. David ATIENZA is a professor of Electrical and Computer Engineering\, and leads both the Embedded Systems Laboratory (ESL) and the new EcoCloud Sustainable Computing Center at EPFL\, Switzerland. He received his M.Sc. and Ph.D. degrees in Computer Science and Engineering from UCM (Spain) and IMEC (Belgium). His research interests include system-level design methodologies for high-performance multi-processor system-on-chip (MPSoC) and low-power Internet-of-Things (IoT) systems\, including edge AI architectures for wearables and IoT systems as well as thermal-aware designs for MPSoCs and many-core servers. He is a co-author of more than 400 papers\, two books\, and has 14 licensed patents in these topics. He served as DATE General Chair and Program Chair\, and is currently Editor-in-Chief of IEEE TCAD and ACM CSUR. Among others\, Dr. Atienza has received the ICCAD 10-Year Retrospective Most Influential Paper Award\, the DAC Under-40 Innovators Award\, the IEEE TC-CPS Mid-Career Award\, and the ACM SIGDA Outstanding Faculty Award. He is a Fellow of IEEE\, a Fellow of ACM\, served as IEEE CEDA President (period 2018-2019) and Chair of the European Design Automation Association (EDAA) in the period 2021-2023. \nOrganizer\nProf. Xianhao CHEN \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240617-1/
LOCATION:Room CPD-3.01\, 3/F\, Run Run Shaw Tower\, The University of Hong Kong
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240628T140000
DTEND;TZID=Asia/Hong_Kong:20240628T160000
DTSTAMP:20260513T031747
CREATED:20240619T032438Z
LAST-MODIFIED:20250114T043256Z
UID:18844-1719583200-1719590400@ece.hku.hk
SUMMARY:A Memristor-based Hybrid Analog-digital Cerebellum (Small Brain) for Mobile Robotics
DESCRIPTION:Abstract\nAlgorithms for mobile robotic systems are generally implemented on purely digital computing platforms. As complementary metal-oxide-semiconductor (CMOS) scaling approaches the end of the road\, the improvement of the throughput of digital processors and computing power efficiency is nearing its end. This issue not only affects the power requirements of large data centers but also limits the performance of mobile robotic systems with perception and actuation. Developing alternative computational platforms may lead to more energy-efficient and responsive mobile robotics. \nInspired by how human and animal brains work\, we report a hybrid analog-digital computing platform enabled by memristors on a mobile inverted pendulum robot. The “cerebellum” (sensor fusion + motion control) of this mobile robotic system is implemented in memristor-based analog circuits\, and the rest of the system is implemented in digital circuits. Such a platform can perform computation in the analog domain and thus removes the speed and energy efficiency bottleneck. The robot using the hybrid analog-digital platform demonstrated dramatic enhancement of speed and energy efficiency over the traditional digital platform. \nSpeaker\nProf. Wei WU\nProfessor\,\nMing Hsieh Department of Electrical and Computer Engineering\,\nUniversity of Southern Californi \nBiography of the Speaker\nProf. Wei WU graduated from Peking University with a BS in Physics in 1996 and received a Ph.D. in Electrical Engineering from Princeton University in 2003. He is a Professor at the Ming Hsieh Department of Electrical and Computer Engineering\, University of Southern California. Before joining USC in 2012\, he had worked as a research associate\, scientist\, and senior scientist at HP labs. His work includes nanoimprint lithography and applications in nano-electronics\, nano-photonics\, plasmonics\, chemical sensing\, and nano-electrochemical cells. He co-authored 126 peer-reviewed scientific journal papers with 12155 citations\, 2 book chapters\, and more than 150 conference presentations\, including 16 keynote and invited presentations. He has 119 granted US patents. Half of them were also filed internationally. His H-index is 503 He is a co-editor of Applied Physics A\, an associate editor of IEEE Transactions on Nanotechnology\, and a regional editor (North America) of Nanomanufacturing and Metrology. He was also an IEEE Nanotechnology Council 2015 and 2016 distinguished lecturer and a recipient of the USC Stevens Center for Innovation Commercialization Award 2020. \nOrganizer\nProf. Han WANG \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240628-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240702T143000
DTEND;TZID=Asia/Hong_Kong:20240702T163000
DTSTAMP:20260513T031747
CREATED:20240619T020036Z
LAST-MODIFIED:20250114T043200Z
UID:18842-1719930600-1719937800@ece.hku.hk
SUMMARY:Magnetism-coupled Flexible and Wearable Devices
DESCRIPTION:Abstract\nThe emergence of flexible and wearable electronics is now leading a revolutionary era for real-time healthcare monitoring and human-machine interaction (HMI) in a more convenient and authentic manner. Sensors\, as the bridge between human beings and electrical terminals\, are playing an important role in facilitating interaction with the complex environment and promoting the healthy development of our society. It is thus crucial to develop high-performance flexible sensors for precise and effective conversion of multiple physiological signals from human beings. In this presentation\, we will introduce our recent studies of magnetism-coupled flexible sensors that aim to improve the sensing performance of flexible devices from linearity\, sensitivity\, to potential working range. Furthermore\, taking advantage of the intrinsic “divergence” and “curl” property of magnetic vector\, we will present that the coupling of magnetized component to flexible sensors can possibly enrich the function for future HMI and healthcare sensing. The design principle and optimization mechanism will be discussed in details. \nSpeaker\nProf. Bingpu ZHOU\nAssociate Professor\,\nInstitute of Applied Physics and Materials Engineering\,\nUniversity of Macau \nBiography of the Speaker\nProf. Bingpu ZHOU obtained his PhD degree from HKUST in 2015. He is currently an Associate Professor of Institute of Applied Physics and Materials Engineering in the University of Macau. He also serves as the Associate Department Head of Department of Physics and Chemistry in Faculty of Science and Technology\, and the Joint Associate Professor in Function Hub at HKUST (GZ). He is recipient of grants including FDCT (Macau SAR)\, GDST (Guangdong\, China) and FDCT-GDST joint projects. His group is mainly focusing on the optimization of flexible sensors with magnetism-mechanics-coupled effect\, and functional surface/interface analysis. He has authored/co-authored ~100 SCI papers. Some of the works have been published in Advanced Materials\, Advanced Functional Materials\, and ACS Nano\, etc. as first/corresponding author. \nOrganizer\nProf. Zhiqin CHU \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240702-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240716T140000
DTEND;TZID=Asia/Hong_Kong:20240716T160000
DTSTAMP:20260513T031747
CREATED:20240702T075019Z
LAST-MODIFIED:20250114T043117Z
UID:18848-1721138400-1721145600@ece.hku.hk
SUMMARY:Introduction to Reinforcement Learning
DESCRIPTION:Abstract\nThis seminar aims to introduce reinforcement learning (RL) and its application to communication systems to graduate students\, although everyone is welcome to attend. RL has successfully been applied to many application domains ranging from control of communication and computer systems\, navigation of driverless vehicles\, robots and flying drones\, to guiding medical imaging and surgery\, to name a few. The speaker will first present the Markov Decision Process (MDP) – the mathematical foundation of RL. To solve the MDP\, the goal is to derive the optimal (action) policy that decides the optimal action for every given state of the system to maximize the long-term reward. As the underlying models for many application settings are unknown\, various model-free RL techniques have been developed\, including temporal difference learning\, SARSA\, Q-learning and policy gradient methods. The speaker will briefly describe these techniques. Furthermore\, as the system complexity increases\, neural networks are used to approximate the Q-values (rewards) and/or action policies as functions of system states and actions. This has led to deep RL where the neural-network parameters are “trained” or “learned” from processing the observed data from practical systems. For illustration purposes\, deep RL is used to manage communication infrastructures. New techniques will be highlighted to overcome issues of model complexity and long training time.  Open research issues on RL will also be briefly discussed. \nSpeaker\nProf. Kin K. LEUNG\nTanaka Chair Professor\,\nElectrical and Electronic Engineering\, and Computing Departments\,\nImperial College\, London \nBiography of the Speaker\nProf. Kin K. LEUNG received his B.S. degree from the Chinese University of Hong Kong\, and his M.S. and Ph.D. degrees from University of California\, Los Angeles. He worked at AT&T Bell Labs and its successor companies in New Jersey from 1986 to 2004. Since then\, he has been the Tanaka Chair Professor in the Electrical and Electronic Engineering (EEE)\, and Computing Departments at Imperial College in London. He also served as the Head of Communications and Signal Processing Group in the EEE Department at Imperial from 2009 to 2024. His current research focuses on optimization and machine learning for system design and control of large-scale communications\, computer and quantum networks. He also works on multi-antenna and cross-layer designs for wireless networks. \nHe is a Fellow of the Royal Academy of Engineering\, IEEE Fellow\, IET Fellow\, and member of Academia Europaea. He received the Distinguished Member of Technical Staff Award from AT&T Bell Labs and the Royal Society Wolfson Research Merits Award. Jointly with his collaborators\, he received the IEEE Communications Society (ComSoc) Leonard G. Abraham Prize (2021)\, the IEEE ComSoc Best Survey Paper Award (2022)\, the U.S.–UK Science and Technology Stocktake Award (2021)\, the Lanchester Prize Honorable Mention Award (1997)\, and several best conference paper awards. He was an IEEE ComSoc Distinguished Lecturer. In 2012-15\, he chaired the IEEE Fellow Evaluation Committee for ComSoc. He has served as an editor for 10 IEEE and ACM journals and chaired the Steering Committee for the IEEE Transactions on Mobile Computing. Currently\, he is an editor for the ACM Computing Survey and International Journal of Sensor Networks. \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240716-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240718T150000
DTEND;TZID=Asia/Hong_Kong:20240718T160000
DTSTAMP:20260513T031747
CREATED:20240529T090712Z
LAST-MODIFIED:20250114T043030Z
UID:18688-1721314800-1721318400@ece.hku.hk
SUMMARY:Quantum Dot-based Opto and Nano Electronic Devices
DESCRIPTION:Abstract\nColloidal quantum dots (QDs) have been of great interest owing to the unique optical and electrical properties\, such as size-dependent band gap tunability\, wide absorption and narrow emission spectra\, and controllable surface properties. Recently\, several types of opto- and nano-electronic devices utilizing QDs have been reported for future optoelectronics. The QD-based light-emitting diodes\, QLEDs\, are one of the most promising devices for future full-color displays and new types of light sources. However\, fundamental mechanisms\, such as charge injection into QDs\, exciton recombination\, and operational stability\, should be understood and improved more to commercialize the QLED displays. In this talk\, I will mainly present our recent research progress on QLEDs\, including device design to improve device performance and to understand operational mechanisms. Also\, I will briefly introduce the QD-based memristors for neuromorphic computing. \nSpeaker\nProf. Jeonghun KWAK\nAssociate Professor\,\nDepartment of Electrical and Computer Engineering\,\nSeoul National University \nBiography of the Speaker\nProf. Jeonghun KWAK received his B.S. (2005) and Ph.D. (2010) degrees in Electrical Engineering from Seoul National University (SNU)\, Korea. After working as a postdoctoral researcher at SNU for one year\, he worked as an assistant/associate professor at Dong-A University\, Korea (2011–2015) and at the University of Seoul\, Korea (2015–2019). Since March 2019\, he has been an associate professor at the Department of Electrical and Computer Engineering\, SNU. His current research interests focus on opto- and nano-electronic devices\, such as QLEDs\, organic thermoelectric devices\, and neuromorphic devices based on organic molecules and low-dimensional materials. \nOrganizer\nProf. Leo Tianshuo ZHAO \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240718-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240802T110000
DTEND;TZID=Asia/Hong_Kong:20240802T120000
DTSTAMP:20260513T031747
CREATED:20240724T043745Z
LAST-MODIFIED:20250114T042912Z
UID:18932-1722596400-1722600000@ece.hku.hk
SUMMARY:High-Frame-Rate Ultrasound Imaging in the Deep Learning Era
DESCRIPTION:Please note the seminar venue is revised to Tam Wing Fan Innovation Wing Two\, The University of Hong Kong. \nAbstract\nUltrasound is undoubtedly a popular medical imaging modality and is becoming known for its high-frame-rate imaging capabilities. However\, high-frame-rate ultrasound has yet to flourish in point-of-care applications due to the lack of suitable portable hardware\, and its ability to offer time-resolved flow visualization is hampered by Doppler aliasing artifacts. Can we take advantage of deep learning to overcome bottlenecks in high-frame-rate system design? Can we design neural networks to resolve Doppler aliasing artifacts in real time? This seminar will introduce our laboratory’s quest to learn deep and learn smart about ultrasound imaging systems to make high-frame-rate ultrasound viable for portable use and flow estimation. We will demonstrate how deep learning solutions can be devised to resolve data transfer bottlenecks in ultrasound systems and\, in turn\, enable robust generation of high-frame-rate ultrasound images with data acquired from few array channels. We will also show how deep learning has enabled the design of advanced Doppler flow imaging platforms with lucid flow visualization performance. Related algorithms\, real-time engineering efforts\, and clinical applications will be presented throughout the presentation. \nSpeaker\nProf. Alfred C. H. YU\nAssistant Vice-President (Research and International)\,\nProfessor of Biomedical Engineering\,\nUniversity of Waterloo\, Canada \nBiography of the Speaker\nProf. Alfred C. H. YU is Assistant Vice-President (Research and International) and Professor of Biomedical Engineering at the University of Waterloo\, Canada. He leads the University of Waterloo’s research partnership portfolio and interdisciplinary research files\, and he is the Director of the NSERC Collaborative Research Program on “Next-Generation Innovations in Ultrasonics” in Canada. Alfred has a long-standing research interest in ultrasound imaging and therapeutics. He is a Fellow of IEEE\, American Institute of Ultrasound in Medicine\, Canadian Academy of Engineering\, and Engineering Institute of Canada. His research has been endorsed by many milestone prizes\, including the NSERC Steacie Memorial Fellowship\, the ISTU Frederic Lizzi Award\, the IEEE Ultrasonics Early Career Investigator Award\, the Ontario Early Researcher Award\, and various best paper awards. He is now the Editor-in-Chief of the IEEE Transactions on Ultrasonics\, Ferroelectrics\, and Frequency Control\, the Program Chair of 2023 and 2025 IEEE Ultrasonics Symposium\, and the Vice-Chair of the AIUM Basic Science and Instrumentation Group. \nOrganiser\nProf. W.-N. LEE \nCo-organisers\nIEEE EMB Hong Kong-Macau Joint Chapter\nTam Wing Fan Innovation Wing Two \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240802-1/
LOCATION:Tam Wing Fan Innovation Wing Two\, G/F\, Run Run Shaw Building\, The University of Hong Kong
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20240808T140000
DTEND;TZID=Asia/Hong_Kong:20240808T170000
DTSTAMP:20260513T031747
CREATED:20240725T085244Z
LAST-MODIFIED:20250114T042822Z
UID:18938-1723125600-1723136400@ece.hku.hk
SUMMARY:MVSG-based Compact Models for GaN Devices
DESCRIPTION:Abstract\nGiven its high mobility\, high breakdown voltage and decent thermal conductivity\, GaN technologies have shown great promise for high-power high-frequency (HP-HF)\, rapidly rising as a front runner for mm-wave to THz analog/RF circuits for IoT and 5G/6G wireless communication. Meanwhile\, it is also heavily explored for power electronic applications for fast charging\, data center\, and electric vehicles. As GaN technology continues to improve\, challenges of high design cost and sub-optimal system performance emerge as bottlenecks preventing the technology from wide scale deployment. Accurate\, scalable and efficient compact model is key to overcome such challenges. \nThis presentation will provide a brief overview of the family of MVSG GaN compact model\, including models for GaN HEMT\, GaN multi-channel diodes and GaN transmission-line resistors.  The model formulation and various features will be introduced. Application examples will also be demonstrated\,  showing the potentials of this group of physics-based compact models. \nSpeaker\nProf. Lan WEI\nAssociate Professor\,\nUniversity of Waterloo\, Canada \nBiography of the Speaker\nProf. Lan WEI received her B.S. in Microelectronics from Peking University\, China (2001)\, M.S and Ph. D. in Electrical Engineering from Stanford University\, USA (2007 and 2010\, respectively). She is currently an Associate Professor at the University of Waterloo\, Canada. She has intensive experience in device physics-based compact modeling including silicon and GaN technologies\, device-circuit interactive design and optimization\, integrated nanoelectronic systems with low-dimensional materials\, cryogenic CMOS device modeling and circuit design for quantum computing.  She has authored/co-authored more than 90 peered reviewed publications and served on the technical program committees including IEDM\, ICCAD\, DATE\, ISQED\, BCICTS\, etc. \nOrganiser\nProf. H. Wang \nCo-organiser\nIEEE ED/SSC Hong Kong Joint Chapter\n\nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240808-1/
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:20240813T143000
DTEND;TZID=Asia/Hong_Kong:20240813T153000
DTSTAMP:20260513T031747
CREATED:20240712T030813Z
LAST-MODIFIED:20250114T042722Z
UID:18871-1723559400-1723563000@ece.hku.hk
SUMMARY:Mechano-nanooncology
DESCRIPTION:Abstract\nNanomedicines are an important means of treating solid tumors\, but in clinical applications\, they can only reduce side effects and cannot significantly improve efficacy. The main reason is that the rapid clearance of the reticuloendothelial system (RES) and the abnormal mechanical microenvironment of solid tumors limit the delivery efficiency of nanomedicines.The RES blockade strategy can temporarily and reversibly delay liver clearance\, improve tumor enrichment and antitumor effects of nanomedicines\, and have good biological safety. However\, the large number of nanoparticles in the circulatory system still imposes an additional burden on RES\, making it particularly important to improve the efficiency of the RES blockade strategy. We systematically explored how to use the mechanical properties of nanogel to overcome the clearing effect of RES\, and proposed the treatment strategy of antitumor effect of nanomedicines with mechanical modulation for the first time. Crucially\, RES blockade strategy based on the mechanical properties of nanogel boosts antitumor efficacy of marketed nanomedicines\, such as Doxil® And Abraxane®. Therefore\, mechano-based RES blockade has broad universality and huge clinical application potential. We propose using hyperbaric oxygen and mild photothermal therapy to improve the abnormal mechanical microenvironment of solid tumors and enhance the antitumor effect of nanomedicines. For the first time\, we discovered that hyperbaric oxygen can overcome tumor hypoxia and inhibit tumor associated fibroblasts\, regulate the abnormal mechanical microenvironment of solid tumors\, as well as the structure and function of tumor blood vessels\, thereby selectively enhancing the commercialized nanomedicines\, e.g.\, Doxil® and Abraxane® and nanoscale biological macromolecules\, such as PD-1 antibodies. In addition\, we have confirmed that the mild photothermal effect of nanomedicines efficiently depletes tumor associated fibroblasts and extracellular matrix\, reduces solid stress and stiffness of tumors\, normalizes tumor vascular structure and function\, promotes subsequent nanomedicine and oxygen delivery\, damages the ecological niche of tumor stem cells\, eliminates cancer stem cells\, and augments the antitumor effect of nanomedicines. Our results indicate that mechano-mediated regulation strategies have the potential to enhance the antitumor effect of nanomedicines. Two prospective trials have been performed in bedside. \nSpeaker\nProf. Zifu LI\nFull Professor\,\nHuazhong University of Science and Technology \nBiography of the Speaker\nProf. Zifu LI received the B.S. degree from Huazhong University of Science and Technology in 2008 and the Ph.D. degree from the Chinese University of Hong Kong in 2012. In 2013 and 2015\, he worked as a postdoctoral fellow at the University of Alberta. He then joined Georgia Institute of Technology as a research scientist. Since 2016\, he has been a full professor at Huazhong University of Science and Technology. Professor Zifu Li’s lab is based on the National Engineering Research Center for Nanomedicine at Huazhong University of Science and Technology. His research lies at the interface of biomaterials\, drug delivery\, and cellular and molecular bioengineering to fundamentally understand and therapeutically target biological molecules\, cancer cells\, immune cells\, and cancer stem cells. He applies his research findings and the technologies developed to a range of human health applications\, particularly on cancer diagnosis and treatment. Current research projects include mechano-nanooncology\, smart nanomedicine and hyperbaric oxygen-enabled cancer therapy. \nOrganizer\nProf. Zhiqin CHU \nAll are welcome! We look forward to seeing you!
URL:https://ece.hku.hk/events/20240813-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Seminar
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END:VCALENDAR