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PRODID:-//Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系 - ECPv6.16.0//NONSGML v1.0//EN
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METHOD:PUBLISH
X-ORIGINAL-URL:https://ece.hku.hk
X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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BEGIN:VTIMEZONE
TZID:Asia/Hong_Kong
BEGIN:STANDARD
TZOFFSETFROM:+0800
TZOFFSETTO:+0800
TZNAME:HKT
DTSTART:20220101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20231101
DTEND;VALUE=DATE:20231102
DTSTAMP:20260513T073710
CREATED:20231030T031257Z
LAST-MODIFIED:20250114T080259Z
UID:17774-1698796800-1698883199@ece.hku.hk
SUMMARY:Machine learning applications to nonlinear pulse propagation dynamics
DESCRIPTION:The propagation of short and intense laser pulses in an optical fiber is known to be associated with a rich landscape of nonlinear propagation scenarios and multidimensional dynamical regimes. For example\, in the coherent regime\, soliton dynamics can lead to the generation of a broadband supercontinuum while in the incoherent regime noise amplification can lead to the development of instabilities that have been associated with the emergence of extreme events. These can be challenging to model and control using conventional approaches. Recently\, there has been rapid growth in the field of smart ultrafast photonics where machine-learning algorithms are combined with nonlinear optical systems allowing for optimized performance and control\, high-speed characterization and identification of particular features within noisy data\, or enhanced functionalities. In this talk\, we will review our work in this area and\, in particular\, we will show how the techniques of machine learning can be efficiently exploited for the analysis of nonlinear instabilities and rogue waves; the prediction of complex supercontinuum generation dynamics with orders of magnitude increased computation speed when compared to conventional direct numerical integration of the generalized nonlinear Schrödinger equation; the optimized and precise control of the spectrum of broadband supercontinuum sources for spectroscopic applications. \nBiography of the speaker: \nGoëry Genty obtained his from Ecole Supérieure d’Optique (France) in 1998 and PhD degree from Aalto University (Finland) in 2004. He has been Professor at Tampere University since 2014. His interest ranges from the study of ultrafast dynamics and instabilities\, supercontinuum generation\, to multimode systems\, real-time measurement techniques\, and machine learning. Awards include the IUPAP Young Scientist International Prize in Optics in 2011 and the Physics Prize of Finnish Academy of Science and Letters in 2019. He is Fellow of the Optical Society of America and European Optical Society and has published more than 150 publications in peer-reviewed journals. Goëry Genty is also the director of the Flagship for Photonics Research and Innovation and director of the Finnish national research infrastructure for light-based technologies\, two of the most prestigious research programs funded by the Research Council of Finland.
URL:https://ece.hku.hk/events/machine-learning-applications-to-nonlinear-pulse-propagation-dynamics/
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20231108T183000
DTEND;TZID=Asia/Hong_Kong:20231108T200000
DTSTAMP:20260513T073710
CREATED:20250224T024610Z
LAST-MODIFIED:20250224T024610Z
UID:110126-1699468200-1699473600@ece.hku.hk
SUMMARY:HKU EEE X HKIE Electrical Membership Drive Talk 2023 (Electrical Discipline)
DESCRIPTION:
URL:https://ece.hku.hk/events/20231108-1/
CATEGORIES:Career Talks,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20231109
DTEND;VALUE=DATE:20231110
DTSTAMP:20260513T073710
CREATED:20231026T033320Z
LAST-MODIFIED:20250114T080234Z
UID:17771-1699488000-1699574399@ece.hku.hk
SUMMARY:IDS Distinguished Speaker Series #4 - Learned Imaging Systems
DESCRIPTION:Computational imaging systems are based on the joint design of optics and associated image reconstruction algorithms. Of particular interest in recent years has been the development of end-to-end learned “Deep Optics” systems that use differentiable optical simulation in combination with backpropagation to simultaneously learn optical design and deep network post-processing for applications such as hyperspectral imaging\, HDR\, or extended depth of field. In this talk I will in particular focus on new developments that expand the design space of such systems from simple DOE optics to compound refractive optics and mixtures of different types of optical components. \nBiography of the speaker: \nProfessor of Computer Science and Elecrical & Computer Engineering @ King Abdullah University of Science and Technology (KAUST) Visual Computing Center\nProf. Wolfgang Heidrich is a Professor of Computer Science and Electrical and Computer Engineering in the KAUST Visual Computing Center\, for which he also served as director from 2014 to 2021. Prof. Heidrich joined King Abdullah University of Science and Technology (KAUST) in 2014\, after 13 years as a faculty member at the University of British Columbia. He received his PhD in from the University of Erlangen in 1999\, and then worked as a Research Associate in the Computer Graphics Group of the Max-Planck-Institute for Computer Science in Saarbrucken\, Germany\, before joining UBC in 2000. Prof. Heidrich’s research interests lie at the intersection of imaging\, optics\, computer vision\, computer graphics\, and inverse problems. His more recent interest is in computational imaging\, focusing on hardware-software co-design of the next generation of imaging systems\, with applications such as High-Dynamic Range imaging\, compact computational cameras\, hyperspectral cameras\, to name just a few. Prof. Heidrich’s work on High Dynamic Range Displays served as the basis for the technology behind Brightside Technologies\, which was acquired by Dolby in 2007.\nProf. Heidrich is a Fellow of the IEEE\, AAIA\, and Eurographics\, and the recipient of a Humboldt Research Award as well as the ACM SIGGRAPH Computer Graphics Achievement Award.
URL:https://ece.hku.hk/events/ids-distinguished-speaker-series-4-learned-imaging-systems/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2024/02/Seminar-s-banner.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20231113
DTEND;VALUE=DATE:20231114
DTSTAMP:20260513T073710
CREATED:20231107T023553Z
LAST-MODIFIED:20250114T080412Z
UID:17811-1699833600-1699919999@ece.hku.hk
SUMMARY:Introduction to the world of optical solitary waves in ultrafast lasers
DESCRIPTION:On the occasion of the 50th anniversary of the prediction of optical solitons\, I feel instructive to revisit the connections between ultrafast laser dynamics and solitary waves through a few milestones. The concepts of conventional (Hamiltonian) and dissipative solitons have been found to echo\, oppose\, or complement each other in the understanding of original dynamical regimes and related optical waveforms – such as bright solitons in normally-dispersive laser cavities\, self-assembled soliton molecules\, and pulsating solitons. Nevertheless\, both concepts remain indispensable in the culture of laser scientists\, as they are actually intertwined in numerous physical situations\, and sustain a remarkable creativity in our scientific field. \nBiography of the speaker: \nPhilippe Grelu received the Ph.D. degree in quantum optics from the University Paris-Saclay in 1996. Following a postdoctoral position at University of Bordeaux\, France\, his interests moved to ultrafast nonlinear optics and femtosecond lasers. He joined the University of Burgundy in 1997 as an Associate Professor\, where he initiated ultrafast fiber laser research and became Full Professor in 2005. He developed a key expertise in nonlinear optical cavity dynamics\, with major contributions in the fast-developing field of dissipative optical solitons. He introduced the use of artificial intelligence\, with genetic algorithms\, to pilot ultrafast fiber lasers. He edited a monograph on Nonlinear Optical Cavity Dynamics in 2016 (Wiley) and is author or coauthor of above 250 scientific articles\, proceedings\, and book chapters.
URL:https://ece.hku.hk/events/introduction-to-the-world-of-optical-solitary-waves-in-ultrafast-lasers/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20231114
DTEND;VALUE=DATE:20231115
DTSTAMP:20260513T073710
CREATED:20231102T074244Z
LAST-MODIFIED:20250114T080350Z
UID:17803-1699920000-1700006399@ece.hku.hk
SUMMARY:On-chip Spectrum Detection and Sub-diffraction Optical Microscopy
DESCRIPTION:Spectral analysis is one of the most widely adopted techniques in various fields of scientific research\, industrial production\, and medical diagnostics. Yet\, traditional spectrum detection techniques often require the setup of spectroscopic components\, photodetector arrays\, and mechanical positioning parts and so on. The relatively large size of those instrumentations may limit their applicability for small-scale or in-situ spectral sensing. In this study\, by leveraging the continuous tunability of the optical bandgap in halide perovskites\, along with the innovation in device architecture/fabrication processes/detection principles\, the authors succeeded to develop single device-based color detectors and integrated flexible spectral sensors. This finding presents promising applications in artificial intelligence vision systems as well as the intelligent sensors in the Internet of Things. \nThough the advanced integrated circuit (IC) fabrication processes are able to fabricate nanoscale devices\, there still remain numerous puzzles in the other domains such as life science\, material science to be explored at nanoscale. In the aim of extending the applicability of advanced IC manufacturing techniques to the other domains\, the authors have developed an ultra-high-density image sensor. After overcoming a series of challenges in semiconductor materials optimization\, photodetector performance improvement\, circuit design\, and sub-wavelength optical physics\, the ultra-high-density image sensor can be utilized in on-chip sub-diffraction optical microscopy. It is expected that this breakthrough will have profound applications in multiple fields such as nanoscience and life science. \nZoom Link :\nhttps://us05web.zoom.us/j/87181504042?pwd=wfGHZAGyUNyUwWiTBHnzgrUtMv9Cra.1 \nMeeting ID: 871 8150 4042\nPasscode: 7zscGQ\n\nBiography of the speaker:\n\nDr. Xiaohan WU\, Associate Professor\, at the School of Microelectronics\, Fudan University\, doctoral advisor. He has been awarded in the Shanghai Young Talents Program and the Shanghai Young Technological Star Program\, and serves as a council member of the Fudan University Young Teachers’ Association. His research focuses on novel image sensors\, advanced memories\, and flexible electronics. Supported by projects from the National Nature Science Foundation and the Minister of Science and Technology of China\, his research works have been published over 60 papers in international academic journals and received more than 10 granted patents.
URL:https://ece.hku.hk/events/on-chip-spectrum-detection-and-sub-diffraction-optical-microscopy/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20231120
DTEND;VALUE=DATE:20231121
DTSTAMP:20260513T073710
CREATED:20231102T032053Z
LAST-MODIFIED:20250114T080326Z
UID:17779-1700438400-1700524799@ece.hku.hk
SUMMARY:Near-Field Communications: What Will Be Different?
DESCRIPTION:In this talk\, the design dilemma of “What will be different between near-field communications (NFC) and far-field communications (FFC)?” is discussed from four perspectives. (1) From the channel modelling perspective\, the differences between near-field and far-field channel models are discussed. (2) From the performance analysis perspective\, analytical results for characterizing the degrees of freedom and the power scaling laws in the near-field region are provided. (3) From the beamforming perspective\, the features of far-field beamsteering and near-field beamfocusing are compared. A couple of new beamforming structures for NFC are also introduced. (4) From the application perspective\, several new designs are discussed in the context of promising next-generation technologies in NFC. Finally\, research opportunities and problem are discussed. \nBiography of the speaker: \nYuanwei Liu is an Associate Professor with 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. His research attract over 20\,000 Google Scholar citations. He is listed as one of 35 Innovators Under 35 China in 2022 by MIT Technology Review and a Web of Science Highly Cited Researcher since 2021. 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.
URL:https://ece.hku.hk/events/near-field-communications-what-will-be-different/
CATEGORIES:Seminar
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20231122
DTEND;VALUE=DATE:20231123
DTSTAMP:20260513T073710
CREATED:20231121T062836Z
LAST-MODIFIED:20250114T080513Z
UID:17850-1700611200-1700697599@ece.hku.hk
SUMMARY:RPG Seminar – Toward Domain Generalization in Stereo Matching Networks
DESCRIPTION:Estimating depth from images is a fundamental problem in many computer vision applications such as autonomous driving and robot navigation. Stereo matching is a solution to this task\, which finds the matching correspondences between stereo image pairs and recovers the depth through triangulation. However\, despite recent stereo matching networks achieving impressive performance given sufficient training data\, they suffer from domain shifts and generalize poorly to unseen domains. In this seminar\, we will review representative works and show some possible improvement directions on domain-generalized stereo matching network. \nZoom Link :\nhttps://hku.zoom.us/j/99189328899?pwd=U291c092a2FrWG03VnB2dGduSkNqUT09 \nBiography of the speaker:\n\nZezheng Zhang received his Bachelor’s from Nankai University in 2020. He is currently pursuing his Ph.D. degree in the Department of Electrical and Electronic Engineering of HKU\, under the supervision of Prof. Kenneth K. Y. Wong. His research interest mainly focus on computer vision and computational imaging. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-toward-domain-generalization-in-stereo-matching-networks/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20231122
DTEND;VALUE=DATE:20231123
DTSTAMP:20260513T073710
CREATED:20231121T063620Z
LAST-MODIFIED:20250114T080539Z
UID:17851-1700611200-1700697599@ece.hku.hk
SUMMARY:RPG Seminar – A Novel Algorithm For TDOA-BASED SOURCE LOCALIZATION with None Line of Sight Error using Robust Least M-estimation
DESCRIPTION:This work presents a novel algorithm for source localization based on Time Difference of Arrival (TDoA) measurements. We proposed a robust variant of the classic least-squares solution that improves the precision and robustness of the localization technique in the presence of heavily noisy measurements\, including those with non-line-of-sight (NLOS) errors\, which could be caused by reverb and reflections. Specifically\, we employ a robust regression algorithm\, namely the Robust Linear Model (RLM)\, to estimate the TDoA values that are used in the least-squares optimization problem. Our proposed RLM-based algorithm is evaluated using both simulations with NLOS error and real-recorded data sets\, and compared with existing methods including conventional least squares(LS) and Regularized Least Squares (RLS) . Simulation results show that our proposed algorithm outperforms existing methods in terms of accuracy and robustness\, especially in highly noisy environments with NLOS error. The use of real-recorded data further demonstrates the effectiveness and practicality of our proposed algorithm. The proposed algorithm has potential applications in acoustic tracking\, speech recognition\, and surveillance\, among others. \nBiography of the speaker:\n\nXiling Sheng completed his Bachelor’s at Commucation University of\nChina\, specializing in Sound Recording Engineering and his MPhil in Technology Leadership and Entreprenurship at HKUST. Currently\, Xiling is a Ph.D. student in the Departmental of Electrical and Electronic Engineering at the University of Hong Kong under the supervision of Prof. Shing Chow Chan. His primary research interest lies in the acoustics\, array signal processing for applications such as tracking\, source seperation and MIMO distribution systems. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-a-novel-algorithm-for-tdoa-based-source-localization-with-none-line-of-sight-error-using-robust-least-m-estimation/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20231129
DTEND;VALUE=DATE:20231130
DTSTAMP:20260513T073710
CREATED:20231123T061424Z
LAST-MODIFIED:20250114T080103Z
UID:17853-1701216000-1701302399@ece.hku.hk
SUMMARY:Web3.0 and Digital Economy
DESCRIPTION:As the world moves towards the new era of post-covid and new world order brought about by innovative industries and digital economy\, Web3.0 serves as the social fabric in everybody’s daily life. \nBiography of the speaker:\n\nProf. James Lei is Secretary General of Institute of Web3.0 Hong Kong\, founder of Meta Metopia\, New Paramount Technology\, and Hunan-Hong Kong Blockchain Institute. He is the Adjunct Professor at HKUST. Before founding Web3.0HK\, he has led Hong Kong Applied Science and Technology Research Institute (ASTRI) for over 18 years in AI\, Big Data\, and intelligent systems. He has worked at Bell Labs\, Lucent Technologies\, Panasonic Research\, and Clicksafe in the U.S. He has over 120 publications and patent applications. He obtained his bachelor’s degree from Beijing University and PhD from Brown University. Prof. Lei actively contributes his experience\, knowledge\, and passion to the technical and innovative entrepreneur world of Web3.0 and digital economy. \nAll are welcome.
URL:https://ece.hku.hk/events/web3-0-and-digital-economy/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20231130
DTEND;VALUE=DATE:20231201
DTSTAMP:20260513T073710
CREATED:20231121T064345Z
LAST-MODIFIED:20250114T080601Z
UID:17852-1701302400-1701388799@ece.hku.hk
SUMMARY:RPG Seminar – Gate anti-screening Effect in InGaZnO Thin‑Film Transistor with High‑κ Gate Dielectric
DESCRIPTION:Gate screening effect has been demonstrated to play a significant role in enhancing the carrier mobility of MOS-based thin-film transistors (TFTs) with high-k gate dielectrics. Typically\, higher gate carrier concentration results in stronger gate screening effect\, leading to increased carrier mobility in the channel layer. However\, recent research has revealed a significant reduction in the channel-carrier mobility of TFT with high-k gate dielectric for specific carrier concentrations in silicon gate. This reduction is believed to be attributed to the resonance between gate-electrode plasmon and gate-dielectric phonon when their frequencies are close/equal\, resulting in the so-called gate anti-screening effect. \nThis seminar aims to provide a comprehensive understanding of the anti-screening effect observed in Indium Gallium Zinc Oxide (IGZO) TFTs employing both single-layered (NdHfO) and double-layered (NdHfO/SiO2) gate dielectrics. The investigation will delve into the underlying physical mechanisms and explore the impact of this phenomenon on the performances of TFT devices. \nZoom Link :\nhttps://hku.zoom.us/j/96298505535 \nMeeting ID: 962 9850 5535\n\nBiography of the speaker:\n\nSun Hao completed his bachelor’s degree from Hunan University\, specializing in electronic and information engineering\, and then obtained his master’s degree from National Space Science Center (NSSC)\, the Chinese Academy of Sciences\, majoring in electronic and communication engineering. Currently\, Sun Hao is a Ph.D. student in the Department of Electrical and Electronic Engineering at the University of Hong Kong\, under the supervision of Prof. P. T. Lai. Mr. Sun’s primary research interest lies in the investigation and modelling of gate screening effect in MOS-based TFTs. \nAll are welcome.
URL:https://ece.hku.hk/events/rpg-seminar-gate-anti-screening-effect-in-ingazno-thin%e2%80%91film-transistor-with-high%e2%80%91%ce%ba-gate-dielectric/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20231130
DTEND;VALUE=DATE:20231201
DTSTAMP:20260513T073710
CREATED:20231123T084723Z
LAST-MODIFIED:20250114T080044Z
UID:17862-1701302400-1701388799@ece.hku.hk
SUMMARY:William Mong Distinguished Lecture: Communication Networks: From Stochastic Models\, to Optimization to Machine Learning
DESCRIPTION:This lecture will briefly overview use of queueing and optimization models to engineer circuit (telephone) and packet-switching networks. It will highlight use of distributed optimization theory\, based on which the well-known Transport Control Protocol (TCP) is shown to allocate communication bandwidth in a distributed and optimal way on the Internet. As for wireless networks\, channel interference and quality of multimedia services complicate resource allocation\, which require new distributed solutions. \nThe speaker will also discuss the relationships between optimization and machine learning (ML). As ML aims to determine the optimal parameters of neural-network models by using the available datasets\, it can also be used to solve general optimization problems.  Ongoing research on applying ML to control future communication networks will be discussed. \nBiography of the speaker: \nKin K. Leung is the Tanaka Chair Professor at Imperial College in London. He received his B.S. from the Chinese University of Hong Kong\, and M.S. and Ph.D. from University of California\, Los Angeles. Before joining Imperial\, he worked at AT&T Bell Labs in New Jersey from 1986 to 2004. He is a Fellow of the Royal Academy of Engineering\, IEEE Fellow\, IET Fellow\, and member of Academia Europaea. His contributions to communication network technologies have led to significant design improvements and new capabilities of nationwide telecommunication systems\, wireless networks\, and defense communication networks\, both in the U.S. and the UK. He has won many professional awards\, including the Bell Labs DMTS Award\, Royal Society Wolfson Research Merit Award\, IEEE Communications Society (ComSoc) Leonard G. Abraham Prize\, IEEE ComSoc Best Survey Paper Award\, and U.S.–UK Science and Technology Stocktake Award. \nAll are welcome. \nRegister Now : https://shorturl.at/gqAS9
URL:https://ece.hku.hk/events/communication-networks-from-stochastic-models-to-optimization-to-machine-learning/
CATEGORIES:Seminar
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