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DTSTART:20190101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190925T110000
DTEND;TZID=Asia/Macau:20190925T120000
DTSTAMP:20260612T054412
CREATED:20190925T030034Z
LAST-MODIFIED:20220927T040649Z
UID:5783-1569409200-1569412800@www.fst.um.edu.mo
SUMMARY:Ecological models and evaluations in a changing environment - a selection from recent results
DESCRIPTION:Instructors/Speakers\nProf. Marta LADANYI\nHead and Assistant Professor\nDepartment of Biometry and Agricultural Informatics\nSzent Istvan University\nHungary \nAbstract\nAgricultural activities are responsible for human well-being while they are facing challenges of increasing impact in a changing environment. Hungary is highly exposed to climate change due to its special location in the middle of Europe. Because of their wide-spread interdependencies\, problems aroused in agriculture need interdisciplinary cooperation to be explored. \nIn our talk\, we introduce some new results from the recent researches performed at Szent Istv´an University\, Faculty of Horticultural Sciences. \nWe outline the structure of some problems and the way of communication between researchers from different disciplines. Questions\, amongst others\, are discussed about \n\nhow to find easily measurable and effective indicators to describe the biodiversity quality of agricultural landscapes or the suitability of agricultural soil;\nhow to measure and manage warming and drought stress from different aspects such as in cases of soil microarthropod communities or medicinal and aromatic plants or invasive pests or the development process and frost volatility of fruit varieties.\n\nWe show the exciting process of how from a complex but well formulated ecology problem we can create a simple mathematical model with which we can highlight the main points of the issue. \nBiography\nProfessor Marta Ladanyi works for Szent István University\, Faculty of Horticulture\, Dpt. of Biometrics and Agricultural Informatics\, Budapest\, Hungary\, Europe. She is an associate professor\, the head of the department. Her special field is applied statistics in life sciences including modelling\, advanced data management and multivariate statistical analysis. \nShe has experience in applications in pomology\, entomology\, plant protection\, soil sciences\, climate change impact studies\, viticulture\, botany\, vegetable\, mushroom\, medical and aromatic plant cultivation\, dendrology etc. She usually uses statistical softwares\, amongst others\, SPSS and R. \nShe has 30 years of teaching experience in applied statistics for BSc\, MSc and PhD students in horticultural studies. Most of her students are Hungarian\, however\, she has several students from several countries\, from time to time\, also from China. \n 
URL:https://www.fst.um.edu.mo/event/ecological-models-and-evaluations-in-a-changing-environment-a-selection-from-recent-results/
LOCATION:E11-1015
CATEGORIES:event_list,math_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190925T140000
DTEND;TZID=Asia/Macau:20190925T150000
DTSTAMP:20260612T054412
CREATED:20190925T060028Z
LAST-MODIFIED:20220927T040648Z
UID:5777-1569420000-1569423600@www.fst.um.edu.mo
SUMMARY:Luminescent Materials
DESCRIPTION:Instructors/Speakers\nProf. Elena V. USHAKOVA\nAssociate Professor\nDepartment of Materials Science and Engineering\nCity University of Hong Kong \nAbstract\nNanostructured hybrid materials nowadays are prospective for utilizing them as an active media in novel photovoltaic and optoelectronic devices\, such as solar cells and light-emitting diodes. An implementing of lead sulfide quantum dots (PbS QDs) and lead-based perovskite films and nanocrystals (NCs) for future photonic devices with a focus on their optical properties will be discussed. \nWhile designing the nanostructured complex materials one of the main points that should be concerned is the interaction of the material compounds which can result\, for instance\, in the desired increase of the charge transfer efficiency or in the uncontrollable quenching of luminophore emission. The enhancement of the optical properties\, such as absorbance and emission of nanoparticles\, is achieved by the fabrication of hybrid material with plasmonic nanoparticles. In particular\, I will discuss strong enhancement of near‐infrared emission of PbS QDs induced by Cu2−xSe semiconductor plasmonic NCs both embedded into nanoporous silicate matrix which comes from resonant interaction of QD optical transition dipole with the near field of plasmons of semiconductor plasmonic NCs. Photocurrent and fill‐factor enhancements in meso‐superstructured perovskite solar cells with resonant silicon NPs resulted in increased light absorption will be also discussed. Another important issue in implementing of the nanostructured materials is the stability of their morphology and optical responses while operating at ambient conditions. Here\, the optical properties of highly luminescent colloidal perovskite NCs (CsPbX3\, where X=Cl/Br\, Br\, I) embedded in porous glass or opal matrices will be discussed. The use of a nanoporous glass or opal matrices allow obtaining the samples with blue\, green\, and red perovskite NCs and their mixtures possessing reproducible optical characteristics that are almost similar to that of colloidal solution. Such matrices also prevent the fast degradation of nanocrystals both at the storage in ambient and under UV-light exposure/increasing of the humidity. \nBiography\nProf. Elena V. Ushakova is currently a Visiting Associate Professor at the Department of Materials Science and Engineering in City University of Hong Kong. She received her PhD in optics at ITMO University in 2013. After that\, she became an Assistant Professor and a Senior Researcher in Prof. Baranov’s group at ITMO University. She has received several personal grants and awards\, including the “St. Petersburg Government Grant for young scientists” and the “Grant of the Russian President for young scientists” (2017-2018). Her research interests are focused on the optical properties of colloidal semiconductor quantum dots\, metal nanoparticles\, perovskite nanocrystals\, carbon dots and self-assembled nanostructured materials with optical transitions in the visible and near infrared region. \n 
URL:https://www.fst.um.edu.mo/event/luminescent-materials/
LOCATION:E11-1028
CATEGORIES:event_list,pc_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190927T143000
DTEND;TZID=Asia/Macau:20190927T153000
DTSTAMP:20260612T054412
CREATED:20190927T063023Z
LAST-MODIFIED:20220927T040648Z
UID:5743-1569594600-1569598200@www.fst.um.edu.mo
SUMMARY:Electron-Lattice Interactions in Lead and Lead-Free Perovskite Single Crystals
DESCRIPTION:Instructors/Speakers\nProf. Bo WU\nProfessor\nSouth China Academy of Advanced Optoelectronics\nSouth China Normal University in Guangzhou\nChina \nAbstract\nRecently\, perovskite materials have gained widespread attentions due to their high potential in optoelectronic applications from solar cells\, light-emitting diodes\, lasers to photodetectors. For example\, the certificated power conversion efficiencies of perovskite solar cells have exceeded 25%\, on par with that of silicon. The external quantum efficiencies of perovskite green and red light emitting diodes have reached 20%\, a value approaching the best performed OLEDs. Despite the rapid progresses in improving the efficiencies\, there remain a lot of questions to be answered about the physical mechanisms lying behind the great successes. In this talk\, I will focus on the interactions between the electrons and the perovskite lattice\, which are complicated by the soft lead-halide bonds\, the hybrid nature of the lattice comprising of both organic and inorganic parts. The talk will be divided into two parts: (1) the thermal-driven dynamical Rashba splitting in lead perovskite single crystals and (2) the strong electron-phonon interactions in bismuth perovskite single crystals. In the first part\, through temperature-dependent photoluminescence\, Raman spectroscopy and molecular dynamical simulations\, we revealed that thermal driven lattice anharmonic polar motions result in dynamical Rashba splitting in lead halide perovskite single crystals\, which may lead to indirect tail states and prolong the carrier lifetimes. In the second part\, through photoluminescence and transient reflection techniques\, we show that a bismuth perovskite single crystal has a carrier mobility of only 0.05 cm2s-1V-1 and relative bright indirect emission\, which imply strong carrier localization effect by the electron-phonon coupling in the system. These findings provide significant insights on the underlying physical mechanisms of perovskites\, which may pave the way to further development of perovskite optoelectronic materials and their commercialization. \nBiography\nProfessor Wu Bo obtained his bachelor degree in Beijing Normal University in 2009 and Ph.D. degree in Nanyang Technological University in 2014. Now he is a professor in the South China Academy of Advanced Optoelectronics\, South China Normal University. His research interest is using spectroscopies and ultrafast spectroscopies to uncover the physical mechanisms of optoelectronic materials and devices\, e.g.\, perovskite solar cells and light emitting diodes\, organic solar cells\, etc. Till now\, he has published more than 40 papers in high-impact journals such as Nature Communications\, Advanced Materials\, Advanced Functional Materials\, ACS Nano etc. He has also published a book on plasmonic organic solar cells and a book chapter on perovskite single crystals in Springer and Wiley\, respectively. \n 
URL:https://www.fst.um.edu.mo/event/electron-lattice-interactions-in-lead-and-lead-free-perovskite-single-crystals/
LOCATION:E11-1028
CATEGORIES:event_list,pc_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20191101T153000
DTEND;TZID=Asia/Macau:20191101T163000
DTSTAMP:20260612T054412
CREATED:20191101T073006Z
LAST-MODIFIED:20220927T040648Z
UID:5753-1572622200-1572625800@www.fst.um.edu.mo
SUMMARY:'Digital Hong Kong' Multi-hazard Risk Evaluation in Extreme Weather Conditions
DESCRIPTION:Instructors/Speakers\nProf. Limin ZHANG\nChair Professor of Geotechnical Engineering\nDirector of Geotechnical Centrifuge Facility\nAssociate Director of Great Smart Cities Institute\nAssociate Head of Department of Civil and Environmental Engineering\nHong Kong University of Science and Technology\nHong Kong \nAbstract\nAn extreme storm may trigger a large number of flood spots\, landslides and debris flows in Hong Kong. The consequences can be catastrophic. To develop strategies to cope with geohazrads induced by extreme rainstorms\, a good understanding of the generation and propagation of hazards during a storm is essential. HKUST is in the process of developing a “Digital Hong Kong” multi-hazard simulation platform to evaluate possible hazardous processes in critical rainstorms in the entire Hong Kong. The simulation framework is introduced and its potential use in enhancing the resilience of Hong Kong is discussed in this seminar. \nBiography\nProf. Limin Zhang is Chair Professor of Geotechnical Engineering\, Director of Geotechnical Centrifuge Facility and Associate Director of Great Smart Cities Institute at the Hong Kong University of Science and Technology. His research areas include slopes\, dams\, geotechnical risk assessment and management\, and centrifuge modeling. Prof. Zhang is Chair of ISSMGE TC210 on Embankment Dams and Chair of ASCE Risk Assessment and Management Committee. He is also Editor-in-Chief of International Journal Georisk\, Associate Editor of ASCE’s Journal of Geotechnical and Geoenvironmental Engineering\, and editorial board member of Engineering Geology\, Computers and Geotechnics and several other journals. \n 
URL:https://www.fst.um.edu.mo/event/digital-hong-kong-multi-hazard-risk-evaluation-in-extreme-weather-conditions/
LOCATION:E11-1009
CATEGORIES:cee_events,event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20191106T103000
DTEND;TZID=Asia/Macau:20191106T113000
DTSTAMP:20260612T054412
CREATED:20191106T023013Z
LAST-MODIFIED:20220927T040647Z
UID:5757-1573036200-1573039800@www.fst.um.edu.mo
SUMMARY:Web Identity Security (WIS) in Big Data Er
DESCRIPTION:Instructors/Speakers\nDr. Wenyin LIU\nWIS Lab\nGuangdong University of Technology \nAbstract\nA web identity is an identifier that uniquely identifies and represents an entity in the Cyberspace. Web identity security focuses on accurate identity verification and prevention of identity impersonation\, fraud\, leakage\, theft\, etc. Nowadays\, the increasing scale of the Web gives rise to the problems of “Password Fatigue”\, “Phishing Attacks” and “Brute Force Password Attacks”\, and brings great challenges to the currently dominant password-based web identity authentication scheme. \nIn this talk\, we will first present the threats and challenges to Web identity security and then introduce our solutions and suggestions. In particular\, we propose a new web identity authentication mechanism by introducing a module named “Trusted User Agent” in the authentication process\, which is compatible with the current password-based mechanism. Specifically\, the user account information is automatically generated by\, stored in the trusted user agent\, and directly sent to the corresponding server\, which authorizes the corresponding session on the specific terminal after successful authentication. This forms a secure closed authentication loop\, in which credentials will never be sent to\, and stolen by phishers at the browser. The proposed mechanism helps users automatically register new accounts with unlinkable identities and strong passwords\, thus free from password cracking. We develop a system based on this mechanism and implement automatic change of passwords as well. Analyses and user studies have been conducted to show its security\, usability\, and deployability\, being superior to the current password-based mechanism. \nA phishing detection mechanism based on parasitic community will then be presented\, which not only reaches an accuracy of 99.2%\, but is the only system in the world capable of discovering phishing targets. A deep learning based solution will also be presented\, which can detect a phishing URL with a very fast speed (20ms) and a very high precision (TPR=98.45% while FPR=0.01%). \nBiography\nDr. Liu Wenyin is currently a Professor in School of Computer Science and Technology\, Guangdong University of Technology. He was Deputy Director of Multimedia software Engineering Research Centre at the City University of Hong Kong from 2013 to 2016\, an assistant professor in the Department of Computer Science at the City University of Hong Kong from 2002 to 2012\, and a full time researcher at Microsoft Research China/Asia from 1999 to 2001. His current research interests include blockchain\, anti-phishing\, Web identity authentication and management. He has BEng and MEng degrees in computer science from Tsinghua University\, Beijing and a doctoral degree from the Technion\, Israel Institute of Technology\, Haifa. In 2003\, he was awarded the IAPR/ICDAR Outstanding Young Researcher Award. In 2010\, he was elected to IAPR Fellow for his contributions to graphics recognition and anti-phishing. He had been TC10 chair of IAPR for two terms 2006-2010. He had been on the IAPR Fellow Committee for three terms 2010-2016. He had been on the editorial boards of the International Journal of Document Analysis and Recognition (IJDAR) from 2006 to 2011 and the IET Computer Vision journal from 2011-2012. He is also an angel investor in the areas of cybersecurity\, blockchain\, big data\, and Robots. \n 
URL:https://www.fst.um.edu.mo/event/web-identity-security-wis-in-big-data-er/
LOCATION:E11-4045 (University of Macau)
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20191108T103000
DTEND;TZID=Asia/Macau:20191108T113000
DTSTAMP:20260612T054412
CREATED:20191108T023057Z
LAST-MODIFIED:20220927T035724Z
UID:5767-1573209000-1573212600@www.fst.um.edu.mo
SUMMARY:The Technology and Application of Speech Translation
DESCRIPTION:Instructors/Speakers\nDr. Boxing CHEN\nMachine Intelligence Lab\nDAMO Academy of Alibaba Group \nAbstract\nWith the significant performance improvement of automatic speech recognition and machine translation\, speech translation comes to the real life from the science fiction. There are two paradigms for speech translation: cascaded and end2end speech translation systems. Due to the size of the available training data\, cascaded speech translation system still over-performs the end2end speech translation system. However\, cascaded speech translation system also suffers the error propagation problem. ASR errors\, punctuation restoration\, language informality\, and disfluency etc. are the main challenges for speech translation. We invest effort in all components of the cascaded speech translation system. We achieve improvement for each component in the pipeline\, therefor result better overall speech translation performance. We show some scenarios at Alibaba\, which we apply speech translation for technical lecture\, communications between buyer and seller\, oversea traveling\, etc. \nBiography\nBoxing Chen is a Senior Algorithm Expert at Machine Intelligence Lab\, DAMO Academy of Alibaba Group. He works on natural language processing\, mainly focus on machine translation. Prior to Alibaba\, he was a Research Officer at the National Research Council Canada (NRC)\, Senior Research Fellow at the Institute for Infocomm Research in Singapore\, a Postdoc at FBK-IRST in Italy and a Postdoc at the University of Grenoble in France. He received his PhD degree from Chinese Academy of Science and Bachelor degree from Peking University in China. He has co-authored more than 50 papers in the NLP conferences and journals. He has received the “The best paper award” from MT Summit 2013\, and “The best paper award nomination” from ACL 2013. His teams ranked the first place in WMT 2018 for five translation tasks and six quality estimation sub-tasks; the first place in WMT 2017 Russian-to-English translation\, the first place in the NIST 2012 OpenMT Chinese-to-English translation\, the first place in the IWSLT 2007 Chinese-to-English translation and IWSLT 2005 Chinese-to-English and Japanese-to-English translation\, etc. \n 
URL:https://www.fst.um.edu.mo/event/the-technology-and-application-of-speech-translation/
LOCATION:E12-G003
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20191108T110000
DTEND;TZID=Asia/Macau:20191108T120000
DTSTAMP:20260612T054412
CREATED:20191108T033908Z
LAST-MODIFIED:20251125T032018Z
UID:5770-1573210800-1573214400@www.fst.um.edu.mo
SUMMARY:The “smart water” application on urban water network distribution real-time monitoring and control system
DESCRIPTION:Instructors/Speakers\nProf. Jeffrey Y. CHENG\nAssociate Professor of Civil Engineering\nSchool of Engineering\nUniversity of Guam\nGuam \nAbstract\nThe “smart water systems” have been introduced to China since 2010 summer in EXPO 2010\, which could be the leading way to improve the urban water distribution problems. In the network age of “4G” going to be “5G”\, leveraging recent advances in technologies surrounding the Internet devices\, urban water distribution systems are poised to transform water supplies management by enabling ubiquitous real-time sensing and control. \nThis paper introduces the methodology of urban water distribution system data collection\, database creation and management\, GIS and BIM applications\, EPA-NET hydraulic and water quality model creation\, real-time sensing and control application. And combined them into a completed real time urban water distribution monitoring program\, the program not only be able to monitoring the metro water distribution but also utilize artificial intelligence (AI) and machine learning to predict the potential issues in the system and provide the optimized solution. \nBiography\nProf. Jeffrey Y. CHENG is currently an Associate Professor of Civil Engineering of the University of Guam. Prof. Cheng obtained his PhD Degree in Civil Engineering from the University of Colorado in 2011. He has been teaching in St Cloud State University\, University of Colorado Denver\, Metro State University of Denver and Los Angeles Pierce College before his current position in University of Guam. Prof. Cheng also has rich industrial experience for over 20 years\, he is currently a senior water resource engineering in Engineering Analytics Inc. Ft Collins CO. Prof. Zhang is working on multiple research projects namely “Flood Mitigation and Water Quality Improvement of City McGregor”\, “Quarry Park and Nature Preserve Water Quality Concern Analysis”\, “Digital Open Channel Flume Design and Construction” \, “Statistical hydrology data analysis for Minnesota regional area” and “Reclamation Action Plan\, Design and Construction of Idorado Mine Site”. \n 
URL:https://www.fst.um.edu.mo/event/the-smart-water-application-on-urban-water-network-distribution-real-time-monitoring-and-control-system/
LOCATION:E11-1009
CATEGORIES:cee_events,event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20191125T113000
DTEND;TZID=Asia/Macau:20191125T123000
DTSTAMP:20260612T054412
CREATED:20191125T033051Z
LAST-MODIFIED:20220927T035724Z
UID:5774-1574681400-1574685000@www.fst.um.edu.mo
SUMMARY:Depth-based Image Processing for Occlusion and Reflection Removal
DESCRIPTION:Instructors/Speakers\nProf. Daniel P. K. LUN\nDepartment of Electronic and Information Engineering\nHong Kong Polytechnic University \nAbstract\nIn 3D computer graphics\, the depth map of a scene is a dataset that provides information about the distance of the surfaces of scene objects from a viewpoint. Nowadays\, we can effectively estimate the depth map of a scene using different hardware or software techniques. It is particularly the case with the recent high-end mobile devices which are all equipped with multiple cameras. The depth map can be estimated using different triangulation methods based on the multiple images captured by the cameras. Once the depth map is obtained\, the next question is what we can do with such additional information of the scene. In this seminar\, the use of the depth information in occlusion removal and reflection removal is discussed. It will be shown that the depth information enables some interesting image processing functions that can hardly be achieved in the past. By using modern data-driven methods\, these depth-based image processing applications can be accomplished within a couple of seconds when running with a GPU. They will be the next applications of modern mobile devices with GPU support. \nBiography\nDaniel\, P.K. Lun received his B.Sc.(Hons.) degree with 1st Class Honours from the University of Essex\, U.K.\, and PhD degree from the Hong Kong Polytechnic University (formerly called Hong Kong Polytechnic) in 1988 and 1991\, respectively. In 1991\, he joined the Hong Kong Polytechnic University\, and is now an Associate Professor and Associate Head of the Department of Electronic and Information Engineering. Dr Lun is active in research. He has published more than 150 international journals and conference papers in the areas of wavelets theory\, signal and image enhancement\, computational imaging and deep neural networks. One of his research projects “A study of the Computer Tomography and the Wavelet Transform” was rate as Excellent by the Hong Kong Research Grants Council. He and his research students have also received three best paper awards in international conferences. Dr Lun was the Chairman of the IEEE Hong Kong Chapter of Signal Processing in 1999-00. He was the General Chair of 2004 International Symposium on Intelligent Multimedia\, Video and Speech Processing (ISIMP 2004)\, and General Co-Chair of 19th International Conference on Digital Signal Processing (DSP 2014). He was also the Technical Co-Chair of 2015 APSIPA Annual Summit and Conference (APSIPA ASC 2015)\, and Technical Co-Chair of 2015 IEEE 20th International Conference on Digital Signal Processing (DSP 2015). He was the executive committee members of a number of other conferences including the 2003 IEEE International Conference on Acoustics\, Speech and Signal Processing (ICASSP 2003)\, 2010 IEEE International Conference on Image Processing (ICIP 2010) and 2017 IEEE International Conference on Multimedia and Expo (ICME 2017). He received the Certificate of Merit from the IEEE Signal Processing Society for dedication and leadership in organizing the 2010 IEEE International Conference on Image Processing (ICIP). He is a member of the IEEE Circuits and Systems Society VSPC and DSP Technical Committees. He was the Editor of HKIE Transactions published by the Hong Kong Institution of Engineers in the area of Electrical Engineering. He was also the leading guest editor of a special issue of EURASIP journal of Advances in Signal Processing. He is currently an Associate Editor of IEEE Signal Processing Letters and IEEE Open Journal of Circuits and Systems. Dr Lun is a Chartered Engineer\, a fellow of IET\, a corporate member of HKIE and a senior member of IEEE. \n 
URL:https://www.fst.um.edu.mo/event/depth-based-image-processing-for-occlusion-and-reflection-removal/
LOCATION:E11-1006 (University of Macau)
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20191128T160000
DTEND;TZID=Asia/Macau:20191128T170000
DTSTAMP:20260612T054412
CREATED:20191128T080029Z
LAST-MODIFIED:20251125T032018Z
UID:5737-1574956800-1574960400@www.fst.um.edu.mo
SUMMARY:BIM and its Development in Hong Kong
DESCRIPTION:
URL:https://www.fst.um.edu.mo/event/bim-and-its-development-in-hong-kong/
LOCATION:E12-G004
CATEGORIES:cee_events,event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20191213T113000
DTEND;TZID=Asia/Macau:20191213T123000
DTSTAMP:20260612T054412
CREATED:20191213T033059Z
LAST-MODIFIED:20220927T035723Z
UID:5732-1576236600-1576240200@www.fst.um.edu.mo
SUMMARY:Deep Feature Encoding for Age-invariant Face Recognition
DESCRIPTION:Instructors/Speakers\nProf. Kin-Man LAM\nThe Hong Kong Polytechnic University \nAbstract\nFacial aging variation is a major problem for face recognition systems\, due to large intra-personal variations caused by age progression. A major challenge is to develop an efficient\, discriminative feature representation and matching framework\, which is robust to facial aging variations. In this talk\, we will present a robust deep-feature encoding-based discriminative model for age-invariant face recognition. Our method learns high-level deep features using a pretrained deep-CNN model. These features are then encoded by learning a codebook with S codewords or atoms\, which converts each of the features into a discriminant S-dimensional codeword for image representation. By incorporating the locality information in the whole learning process\, a closed-form solution is obtained for both the codebook-updating and encoding stages. Furthermore\, as the features of the same person at different ages should have certain correlations\, canonical correlation analysis is utilized to fuse the pair of training features from the same person\, but at two different ages\, to make the codebook discriminative in terms of age progression. In the testing stage\, the gallery and query image’s features are encoded using the learned codebook. Then\, linear mapping based on linear regression is employed for face matching. We will present the performance of the method on three publicly available challenging facial aging datasets\, FGNET\, MORPH Album 2\, and Large Age-Gap. \nBiography\nProf. Kin-Man Lam received his Associateship in Electronic Engineering with distinction from the Hong Kong Polytechnic University (formerly called Hong Kong Polytechnic) in 1986. He won the S.L. Poa Education Foundation Scholarship for overseas studies and was awarded an M.Sc. degree in communication engineering from the Department of Electrical Engineering\, Imperial College of Science\, Technology and Medicine\, England\, in 1987. In August 1993\, he undertook a Ph.D. degree program in the Department of Electrical Engineering at the University of Sydney\, Australia\, and won an Australia Postgraduate Award for his studies. He completed his Ph.D. studies in August 1996\, and was awarded the IBM Australia Research Student Project Prize. \nProf. Lam joined the Department of Electronic and Information Engineering\, The Hong Kong Polytechnic University as an Assistant Professor in October 1996. He became an Associate Professor in 1999\, and has been a Professor since 2010. Currently\, he is also an Associate Dean of the Faculty of Engineering. He was actively involved in professional activities. He has been a member of the organizing committee or program committee of many international conferences. In particular\, he was the Technical Chair of the 2004 International Symposium on Intelligent Multimedia\, Video and Speech Processing (ISIMP 2004)\, a Technical Co-Chair of the 2005 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS 2005) and 2010 Pacific-Rim Conference on Multimedia (PCM 2010)\, and a General Co-Chair of the 2012 IEEE International Conference on Signal Processing\, Communications\, & Computing (ICSPCC 2012)\, the APSIPA Annual and Summit 2015 (APSIPA ASC 2015)\, and the 2017 IEEE International Conference on Multimedia and Expo (ICME 2017)\, which were held in Hong Kong in August 2012\, December 2015\, and July 2017. Prof. Lam was the Chairman of the IEEE Hong Kong Chapter of Signal Processing between 2006 and 2008. He received an Honorable Mention of the Annual Pattern Recognition Society Award for an outstanding contribution to the Pattern Recognition Journal in 2004. \nProf. Lam was the Director-Student Services and the Director-Membership Services of the IEEE Signal Processing Society between 2012 and 2014\, and between 2015 and 2017\, respectively. He was an Associate Editor of IEEE Trans. on Image Processing between 2009 and 2014\, an Associate Editor of Digital Signal Processing between 2014 and 2018\, an Editor of HKIE Transactions between 2013 and 2018\, and an Area Editor of the IEEE Signal Processing Magazine between 2015 and 2017. Currently\, he is the VP-Publications of the Asia-Pacific Signal and Information Processing Association (APSIPA). Prof. Lam serves as an Associate Editor of APSIPA Trans. on Signal and Information Processing and EURASIP International Journal on Image and Video Processing. His current research interests include human face recognition\, image and video processing\, and computer vision. \n 
URL:https://www.fst.um.edu.mo/event/deep-feature-encoding-for-age-invariant-face-recognition/
LOCATION:E11-4045 (University of Macau)
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20191219T110000
DTEND;TZID=Asia/Macau:20191219T120000
DTSTAMP:20260612T054412
CREATED:20191219T030022Z
LAST-MODIFIED:20220927T035723Z
UID:2014-1576753200-1576756800@www.fst.um.edu.mo
SUMMARY:Sift Sand for Gold: Towards Research Challenges in Big Video Data Computing
DESCRIPTION:Instructors/Speakers\nProf. Wenbo HE\nMcMaster University\nCanada \nAbstract\nNowadays\, billions of videos are captured\, hosted and shared in the cloud\, and the world has stepped into a multimedia big data era. As an active and interdisciplinary research field\, multimedia big data presents great challenges and opportunities for multimedia big data computing. A vast amount of research work has been done in image processing\, targeting different aspects of big data analytics\, such as the capture\, storage\, indexing\, mining\, and retrieval. However\, when shifting the attention from images to videos\, we are facing several challenges (e.g. it is more challenging to generate video features with temporal correlation; it is more challenging to get correctly labeled video samples for machine learning algorithms; etc.). In this talk\, I will mention several of our recent and on-going projects addressing these challenges\, and discuss potential future directions in video big data analytics. \nBiography\nDr. Wenbo He is currently an Associate Professor in the Department of Computing and Software at McMaster University. Before that she was an Assistant Professor in School of Computer Science at McGill University from 2011 to 2015\, an Assistant Professor in the EE department at the University of Nebraska-Lincoln from 2010 to 2011\, and an Assistant Professor in the CS department at the University of New Mexico from 2008 to 2010. She had 5-year industry experience (2000-2005) working in Cisco Systems\, Inc. in the US. She got the Bachelor and Master Degree on Control Theory in 1995 and 1998 respectively. She got her Ph.D. in 2008 from the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC). She received the Mavis Memorial Fund Scholarship Award from the College of Engineering of UIUC in 2006 for “excellent academic performance\, research accomplishments\, and demonstrated leadership in engineering education”\, and the C. W. Gear Outstanding Graduate Award in 2007 for “being one of the best graduate students from the UIUC Department of Computer Science”. She was also a recipient of the prestigious Vodafone Fellowship from 2005 to 2008 for 3 consecutive years\, and NSF TRUST Fellowship in 2007& 2009 respectively. Her papers won the Best Paper Award from IEEE Transactions on Industrial Informatics in 2008\, and the Best Paper Award from ACM WiSec 2011 (ACM Conference on Security and Privacy in Wireless and Mobile Networks). Her research focuses include big data systems\, pervasive & mobile computing\, and information privacy and security.
URL:https://www.fst.um.edu.mo/event/sift-sand-for-gold-towards-research-challenges-in-big-video-data-computing/
LOCATION:E11-1006
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20200110T110000
DTEND;TZID=Asia/Macau:20200110T120000
DTSTAMP:20260612T054412
CREATED:20200110T030012Z
LAST-MODIFIED:20220927T035722Z
UID:5727-1578654000-1578657600@www.fst.um.edu.mo
SUMMARY:High-dimensional vector autoregressive time series modeling via tensor decomposition
DESCRIPTION:Instructors/Speakers\nProf. Guodong LI\nAssociate Professor\nDepartment of Statistics & Actuarial Science\nUniversity of Hong Kong\nHong Kong \nAbstract\nThe classical vector autoregressive model is a fundamental tool for multivariate time series analysis. However\, it involves too many parameters when the number of time series and lag order are even moderately large. This paper proposes to rearrange the coefficient matrices of the model into a tensor form such that the parameter space can be restricted in three directions simultaneously via tensor decomposition. The proposed method substantially expands the capacity of vector autoregressive modeling for a large number of time series. In contrast\, the widely used reduced-rank regression method can restrict the parameter space in only one direction. Moreover\, to handle high-dimensional time series\, this paper considers imposing sparsity on factor matrices to improve the interpretability and estimation efficiency\, which leads to a sparsity-inducing estimator. For the low-dimensional case\, we derive asymptotic properties of the proposed least squares estimator and introduce an alternating least squares algorithm. For the high-dimensional case\, we establish non-asymptotic properties of the sparsity-inducing estimator and propose an ADMM-based algorithm for regularized estimation. Simulation experiments and a real data example demonstrate the advantages of the proposed approach over various existing methods. \nBiography\nProf. Li received his PhD at The University of Hong Kong and is an associate professor at The University of Hong Kong. Prof. Li research fields include high dimensional statistics\, econometrics\, machine learning. He has published nearly 50 papers on international journals such as Annals of Statistics\, JRSS-B\, Biometrika\, JASA and so on. \n 
URL:https://www.fst.um.edu.mo/event/high-dimensional-vector-autoregressive-time-series-modeling-via-tensor-decomposition/
LOCATION:E11-1012
CATEGORIES:event_list,math_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20201110T160000
DTEND;TZID=Asia/Macau:20201110T170000
DTSTAMP:20260612T054412
CREATED:20201109T031523Z
LAST-MODIFIED:20251125T032009Z
UID:9535-1605024000-1605027600@www.fst.um.edu.mo
SUMMARY:Markov chain Monte Carlo based Bayesian method for railway ballast damage detection
DESCRIPTION:
URL:https://www.fst.um.edu.mo/event/markov-chain-monte-carlo-based-bayesian-method-for-railway-ballast-damage-detection/
LOCATION:E11-1021\, Macau
CATEGORIES:cee_events,event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210401
DTEND;VALUE=DATE:20210409
DTSTAMP:20260612T054412
CREATED:20210401T045441Z
LAST-MODIFIED:20220927T034543Z
UID:16497-1617235200-1617926399@www.fst.um.edu.mo
SUMMARY:2021 Bank of China Macau Branch Recruitment - Positions for Information Technology
DESCRIPTION:中國銀行澳門分行2021年春季校園招聘已開始接受報名，本次共有四個崗位供同學選擇，而信息科技崗為重點招聘崗位之一，讓更多有需要的同學獲取更多、更佳的就業機會，使同學能於職業道路上學以致用、一展所長!\n招聘對象：2020、2021年的畢業生​ \n截止時間：2021年4月8日 （星期四）24:00\n連結：​https://mp.weixin.qq.com/s/Dn2eI7Tt4pkpwrp8qzKGiQ\n報名連結：http://campus.chinahr.com/views/2021/boc-spring/index.html\n報名攻略：https://b.xiumi.us/board/v5/4tQZC/275688846\n筆試日期：4月中下旬（暫定）\n筆試形式：待定​ \n如有任可疑問或需要更多資訊，歡迎電郵至recruit@bocmacau.com或致電(853)8792    0809與趙小姐聯繫
URL:https://www.fst.um.edu.mo/event/2021-bank-of-china-macau-branch-recruitment-positions-for-information-technology/
LOCATION:Online
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210408T140000
DTEND;TZID=Asia/Macau:20210409T150000
DTSTAMP:20260612T054412
CREATED:20210401T050338Z
LAST-MODIFIED:20220927T034543Z
UID:16507-1617890400-1617980400@www.fst.um.edu.mo
SUMMARY:UM-SIAT Workshop on Cooperative Innovation between Information Technology and Life Science
DESCRIPTION: \n \n \n \n \n \n \n \n \n \n \n \n \n \n  \n 
URL:https://www.fst.um.edu.mo/event/um-siat-workshop-on-cooperative-innovation-between-information-technology-and-life-science/
LOCATION:N21-5007
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210416T161500
DTEND;TZID=Asia/Macau:20210416T171500
DTSTAMP:20260612T054412
CREATED:20210413T101357Z
LAST-MODIFIED:20220927T034543Z
UID:16638-1618589700-1618593300@www.fst.um.edu.mo
SUMMARY:SKL-IOTSC Talk Series: Computational Social Choice: Algorithms for Fair Allocation Problems智慧城市物聯網系列講座: 計算社會選擇理論: 多智能體均分問題
DESCRIPTION:是次講座在4月16日舉行，並由電腦及資訊科學系吳曉偉教授主講\nSKL-IoTSC Talk series: Computational Social Choice: Algorithms for Fair Allocation Problems\n智慧城市物聯網系列講座: 計算社會選擇理論: 多智能體均分問題\n· 日期 Date : 2021.04.16 (Friday)\n· 時間 Time : 16:15 – 17:15\n· 語言 Language : 英語 English\n· 地點 Venue : N21 5樓展覽廳N21-5/F EXHIBITION HALL\nRemark: maximum capacity: 50 pax; first come first serve\n \n\n\n吳曉偉教授於2020年3月加入澳大，成為科技學院電腦及資訊科學系助理教授及智慧城市物聯網國家重點實驗室成員。吳曉偉教授的論文《全面線上配對》獲發表在最新一期的ACM期刊上 (Journal of ACM)。ACM期刊被公認是理論計算機科學領域最頂尖的期刊，此期刊只登載那些對計算機科學有深遠影響的論文，此期刊過去十年總收錄文章不足400篇，其中僅有15篇來自中國（包括港澳台）地區。吳教授的論文也是過去十年澳門地區發表於該期刊的第一篇文章\n \n\n\nProf. Xiaowei Wu joined UM in 2020. He is an assistant professor in the Department of Computer and Information Science\, and the research member of the State Key Laboratory of Smart City Internet of Things. Prof. Wu’s article “Fully online matching” was published in the latest issue of the Journal of ACM (JACM)\, which is considered a top journal in the field of theoretical computer science that only publishes papers with a profound impact on the field. In the past decade\, Journal of ACM has published less than 400 articles\, of which only 15 come from China (including Hong Kong\, Macao\, and Taiwan). It is also the first paper from Macao that has been published in this journal in the past decade\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n  \n 
URL:https://www.fst.um.edu.mo/event/skl-iotsc-talk-series-computational-social-choice-algorithms-for-fair-allocation-problems/
LOCATION:N21- 5/F Exhibition Hall
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210430T160000
DTEND;TZID=Asia/Macau:20210430T180000
DTSTAMP:20260612T054412
CREATED:20210429T065732Z
LAST-MODIFIED:20220927T034543Z
UID:16819-1619798400-1619805600@www.fst.um.edu.mo
SUMMARY:SKL-IOTSC Talk Series: Social Media Mining and Representation Learning from High-Dimensional\, Dynamic and Complex Data 智慧城市物聯網系列講座: 社交媒體挖掘及複雜數據表示學習
DESCRIPTION:兩位科技學院教授獲邀在智慧城市物聯網系列講座上分享社交媒體及數據表示學習的知識\, 包括鞏志國教授(社交媒體挖掘) 及楊丁奇副教授 (複雜數據表示學習)\n\n\n日期Date: 2021.04.30 (Friday)\n時間Time: 16:00 – 18:00\n地點Venue: N21 5樓展覽廳 N21-5/F EXHIBITION HALL\n語言Language: 英語English\n\n\nRemark: maximum capacity: 50 pax; first come first serve\n\n \n人物簡介:\n鞏志國教授是電腦及資訊科學系的學系主任，1998年於中國科學院大學畢業，1999年加入澳大並擔任助理教授，現己是正教授的鞏志國教授研究領域包括機器學習\, 數據挖掘\, 數據庫\, 信息檢索等。\nProf. Gong Zhiguo is the Department head of the department of Computer and Information Science. He graduated from Chinese Academy of Sciences in 1998 and joined UM in 1999 as an Assistant Professor. Prof. Gong Zhiguo is now a full professor and his research interest are  machine learning\, data mining\, databases and Information retrieval.\n \n\n楊丁奇教授2015年於 Telecom SudParis／Pierre and Marie Curie University (Paris 6) 取得計算機科學博 士 學 位。他 的 研 究 領 域 是 設 計 新 穎 的 數 據 挖 掘 和 機 器 學 習 技 術，並 為 現 實 世 界 的 智 能 城 市 應 用程 序 構 建 實 用 系 統。\nProf. Yang Dingqi graduated from the Telecom SudParis／Pierre and Marie Curie University (Paris 6)\, France in 2015 wtih a PhD degree in Computer Science. His research interests are design novel data mining and machine learning techniques for urban big data analytics and build up practical systems for real-world smart city applications.
URL:https://www.fst.um.edu.mo/event/skl-iotsc-talk-series-social-media-mining-and-representation-learning-from-high-dimensional-dynamic-and-complex-data/
LOCATION:N21- 5/F Exhibition Hall
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210521T160000
DTEND;TZID=Asia/Macau:20210521T180000
DTSTAMP:20260612T054412
CREATED:20210520T034612Z
LAST-MODIFIED:20220927T034541Z
UID:16982-1621612800-1621620000@www.fst.um.edu.mo
SUMMARY:SKL-IOTSC Talk Series: Tunnel Engineering – From Physics to Big Data and Multi-scale Modelling of Flood Hazards 智慧城市物聯網系列講座: 隧道工程 － 從物理現象到大數據及多尺度洪澇災害數值模擬
DESCRIPTION:兩位科技學院教授獲邀在智慧城市物聯網系列講座上分享相關領域的專業知識\, 周萬歡副教授將分享隧道工程 － 從物理現象到大數據 及高亮助理教授將分享多尺度洪澇災害數值模擬\n日期Date: 2021.05.21 (Friday)\n時間Time: 16:00 – 18:00\n地點Venue: N21 5樓展覽廳 N21-5/F EXHIBITION HALL\n語言Language: 英語English \n\n人物簡介: 周萬歡教授於2002年及2005年獲浙江大學本科及碩士學位並於2008年獲香港理工大學博士學位。 曾於香港理工大學土木及結構工程系擔任講師。 2009年加入澳門大學，現擔任澳大土木與環境工程系主任、澳大區域海洋中心代主任及智慧城市物聯網國家重點實驗室成員之一。主要研究領域包括：岩土材料的本構模、岩土工程中的數值建模、地面改良（土釘，樁承路堤，土工合成材料等）、岩土工程中的概率分析等。Prof. Zhou Wanhuan received a bachelor’s degree and a master’s degree from Zhejiang University in 2002 and 2005\, and a doctorate degree from the Hong Kong Polytechnic University in 2008. She worked as a Lecturer in the Department of Civil and Structural Engineering of the Hong Kong Polytechnic University. She joined the University of Macau in 2009 and is currently the Department Head of the Department of Civil and Environmental Engineering of FST\, the intern director of the Centre for Regional Oceans\, she is also one of the member of the State Key Laboratory of Smart City Internet of Things. Her research areas are Constitutive Modeling of Geomaterials\, Numerical Modeling in Geotechnical Engineering and Ground Improvement (Soil nails\, pile-supported embankment\, geosynthetics\, etc) and Probabilistic Analysis in Geotechnical Engineering\, etc. \n\n\n\n高亮教授在2009及2011年獲清華大學本科及碩士學位，曾任職浙江省水利河口研究院\, 2016年在香港科技大學土木工程博士畢業，曾任香港科技大學博士後研究員及美國俄克拉荷馬大學國家氣象中心博士後研究員。現擔任澳大科技學院土木及環境工程系的助理教授，同時也是智慧城市物聯網國家重點實驗室及海洋區域研究中心的研究成員之一。Prof. Gao Liang received her bachelor and master degree from Tsinghua University in 2009 and 2011. In 2016\, she graduated from Hong Kong University of Science and Technology with a Ph.D. degree in civil engineering. After that\, she worked as a post-doctoral researcher at Hong Kong University of Science and Technology and Oklahoma\, USA Postdoctoral researcher at the University’s National Meteorological Center. She is currently an Assistant professor in the Department of Civil and Environmental Engineering of the Faculty of Science and Technology and also one of the research members of the State Key Laboratory of Smart City Internet of Things and the Centre for Regional Oceans. \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 
URL:https://www.fst.um.edu.mo/event/skl-iotsc-talk-series-tunnel-engineering-from-physics-to-big-data-and-multi-scale-modelling-of-flood-hazards/
LOCATION:N21- 5/F Exhibition Hall
CATEGORIES:cee_events,event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210526
DTEND;VALUE=DATE:20210621
DTSTAMP:20260612T054412
CREATED:20201125T044758Z
LAST-MODIFIED:20220927T034541Z
UID:13700-1621987200-1624233599@www.fst.um.edu.mo
SUMMARY:Paper Submission for 2021 7th International Conference on  Innovation and Industrial Logistics (Deadline: 20 June 2021)
DESCRIPTION: \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n  \n 
URL:https://www.fst.um.edu.mo/event/paper-submission-for-2021-7th-international-conference-on-innovation-and-industrial-logistics/
LOCATION:Online
CATEGORIES:ece_events,event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210621T093000
DTEND;TZID=Asia/Macau:20210621T103000
DTSTAMP:20260612T054412
CREATED:20210621T033555Z
LAST-MODIFIED:20220927T034540Z
UID:17418-1624267800-1624271400@www.fst.um.edu.mo
SUMMARY:The ParaDiag Algorithm
DESCRIPTION:Instructors/Speakers\nProf. Shu-Lin WU\nProfessor\nSchool of Mathematics and Statistics\nNortheast Normal University\nChangchun\, Jilin\, China \nAbstract\nThe mainstream parallel-in-time (PinT) algorithms\, such as parareal and MGRiT\, cannot efficiently handle the wave propagation problems\, due to the poor convergence rate (or even divergence). New PinT algorithms are proposed in recent years and have shown promising advantages. These new PinT algorithms are called ParaDiag\, which was permitted in 2020 by the PinT scientific committee to show and popularize on the homepage of this filed (http://parallel-in-time.org/codes/paradiag.html). In this talk we will discuss some variants and introduce some basic theoretical results. \nBiography\nProf. Shulin WU obtained his Ph.D. degree in Huazhong University of Science and Technology in 2010. From 2010 to 2016\, he did post-doctoral research at University of Electronic Science and Technology of China\, University Of Geneva and The Hong Kong Polytechnic University. His research interests are Parallel-in-Time algorithms\, waveform relaxation\, numerical analysis of DLCP/DNCP problems and numerical wave propagation. Prof. Wu Shulin works as a Professor at Northeast Normal University now\, published more than 30 papers on many international famous SCI journals of computing\, such as J. Comp. Phys.\, J. Sci. Comp.\, SIAM J. Control and Optimization. \n 
URL:https://www.fst.um.edu.mo/event/the-paradiag-algorithm/
LOCATION:E11-1006
CATEGORIES:event_list,math_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210621T104000
DTEND;TZID=Asia/Macau:20210621T114000
DTSTAMP:20260612T054412
CREATED:20210621T034649Z
LAST-MODIFIED:20220927T034540Z
UID:17420-1624272000-1624275600@www.fst.um.edu.mo
SUMMARY:Sharp pointwise-in-time error estimate of L1 scheme for nonlinear subdiffusion equations
DESCRIPTION:Instructors/Speakers\nProf. Dongfang LI\nProfessor\nSchool of Mathematics and Statistics\nHuazhong University of Science and Technology\nChina \nAbstract\nAn essential feature of the subdiffusion equations with the α-order time fractional derivative is the weak singularity at the initial time. The weak regularity of the solution is usually characterized by a regularity parameter δ∈(0\,1)∪(1\,2). Under this general regularity assumption\, we present a rigorous analysis for the truncation errors and develop a new tool to obtain the stability results\, i.e.\, a refined discrete fractional-type Gronwall inequality. After that\, we obtain the pointwise-in-time error estimate of the widely used L1 scheme for nonlinear subdiffusion equations. The present results fill the gap on some interesting convergence results of L1 scheme on δ∈(0\,α)∪(α\,1)∪(1\,2]. Numerical experiments are provided to demonstrate the effectiveness of our theoretical analysis. \nBiography\nProf. Dongfang LI obtained his Ph.D. degree in Huazhong University of Science and Technology in 2011 and did post-doctoral research at McGill University and City University of Hong Kong. His main research interests include numerical analysis \, fractional differential equations\, etc.\nHe is a professor at the School of Mathematics and Statistics\, Huazhong University of Science and Technology\, has published more than 30 papers on many international famous SCI journals of computing\, such as J. Comp. Phys.\, Appl. Comp. Harm. Appl.\, J. Sci. Comp.\n \n 
URL:https://www.fst.um.edu.mo/event/sharp-pointwise-in-time-error-estimate-of-l1-scheme-for-nonlinear-subdiffusion-equations/
LOCATION:E11-1006
CATEGORIES:event_list,math_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210621T143000
DTEND;TZID=Asia/Macau:20210621T153000
DTSTAMP:20260612T054412
CREATED:20210621T034921Z
LAST-MODIFIED:20220927T034540Z
UID:17422-1624285800-1624289400@www.fst.um.edu.mo
SUMMARY:Fast convolution quadrature for the fractional operators
DESCRIPTION:Instructors/Speakers\nProf. Fanhai ZENG\nProfessor\nSchool of Mathematics\nShandong University\nChina \nAbstract\nWe develop two fast memory saving methods for calculating the fractional integral and derivative operators. \nFast Method I is based on a local approximation for the contour integral that represents the convolution weight. Fast Method II is based on a globally uniform approximation of the trapezoidal rule for the integral on the real line. Both methods are efficient\, but numerical experimentation reveals that Fast Method II outperforms Fast Method I in terms of accuracy\, efficiency\, and coding simplicity for dealing with the fractional derivative operator. Our fast method simplifies the existing one [SIAM J. Sci. Comput.\, 28 (2006)\, pp. 421–438].\n \nBiography\nProf. Fanhai ZENG received his bachelor degree from Northwestern Polytechnical University in 2005. In 2014\, he graduated from Shanghai University with a Ph.D. degree. His research interest is in computational mathematics and fractional differential equations. He works as a Professor at Shandong University.\nFrom 2014 to 2020\, he did post-doctoral research at Brown University in the United States\, Queensland University of Technology in Australia and the National University of Singapore. He co-published a monograph in 2015\, won the Shanghai Excellent Doctoral Dissertation Award in 2016\, published more than 30 papers in international journals such as SINUM\, SISC\, JSC\, JCP and CMAME\, and was cited by SCIE more than 1\,000 times. \n \n 
URL:https://www.fst.um.edu.mo/event/fast-convolution-quadrature-for-the-fractional-operators/
LOCATION:E11-1006
CATEGORIES:event_list,math_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210621T154000
DTEND;TZID=Asia/Macau:20210621T164000
DTSTAMP:20260612T054412
CREATED:20210621T035226Z
LAST-MODIFIED:20220927T034539Z
UID:17424-1624290000-1624293600@www.fst.um.edu.mo
SUMMARY:Low-rank modified Douglas splitting methods for differential matrix equations
DESCRIPTION:Instructors/Speakers\nProf. Hao CHEN\nAssociate Professor\nChongqing Normal University\nChongqing\, China \nAbstract\nIn this talk\, we consider a modified Douglas splitting method for a class of differential matrix equations\, including differential Lyapunov and differential Riccati equations. The method we consider is based on a natural three-term splitting of the equations. The implementation of the algorithm requires only the solution of a linear algebraic system with multiple right-hand sides in each time step. It is proved that the method is convergent of order two and it preserves the symmetry and positive semidefiniteness of solutions of differential Lyapunov equations. Moreover\, we show how the method can be handled in a low-rank setting for large-scale computations. We also provide a theoretical a priori error analysis for the low-rank algorithms. Numerical results are presented to verify the theoretical analysis.\n \nBiography\nProf. Hao CHEN received his B.Sc. and Ph.D. from Huazhong University of Science and Technology in 2007 and 2012. His research interest is in “Numerical algorithms for partial differential equations\, Numerical algorithms for integro-differential equations\, numerical linear algebra\, PDE constrained optimization”. He works as an Associate Professor at Chongqing Normal University. \nProf. Chen Hao is the member of the Professional Committee of Chinese Simulation Algorithms\, Commentator of the American Mathematical Review. He has published more than 20 papers in international computational mathematics journals such as “J. Comput. Phys.”\, “J. Sci. Comput.”\, “BIT Numer. Math.”.
URL:https://www.fst.um.edu.mo/event/low-rank-modified-douglas-splitting-methods-for-differential-matrix-equations/
LOCATION:E11-1006
CATEGORIES:event_list,math_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210621T165000
DTEND;TZID=Asia/Macau:20210621T175000
DTSTAMP:20260612T054412
CREATED:20210621T035427Z
LAST-MODIFIED:20220927T034539Z
UID:17426-1624294200-1624297800@www.fst.um.edu.mo
SUMMARY:Pointwise error estimates of the novel nonlinear fourth-order compact difference scheme for viscous Burgers’ equation
DESCRIPTION:Instructors/Speakers\nProf. Qifeng ZHANG\nAssociate Professor\nZhejiang Sci-Tech University\nChina \nAbstract\nIn this talk\, a novel fourth-order three-point compact operator for the nonlinear convection term is provided. The operator makes the numerical analysis of higher order nonlinear or linearly implicit difference schemes become possible for a wide class of nonlinear evolutionary equations under the unified framework. We take the classical viscous Burgers’equation as an example and establish a new conservative fourth-order implicit compact difference scheme based on the method of order reduction. A detailed theoretical analysis is carried out. Furthermore\, we derive a three-level linearized compact difference scheme for viscous Burgers’equation based on the proposed operator. Applying the compact operator to other more complex and higher-order nonlinear evolutionary equations is feasible\, including Benjamin-Bona-Mahony-Burgers’equation\, Korteweg-de Vries equation\, Kuramoto-Sivashinsky equation\, and classification to name a few. Numerical results confirm our results.\n \nBiography\nProf. Qifeng ZHANG obtained his Ph.D. degree in Huazhong University of Science and Technology in 2014\, works as an associate professor at Zhejiang Sci-Tech University. His main research interests include high-order numerical methods for delay PDEs and fractional PDEs\, numerical solution for nonlinear evolutionary equations\, preconditioning techniques and iterative methods for PDEs\, etc. He has presided over one project of National Natural Science Foundation of China and two projects of Zhejiang Provincial Natural Science Foundation \, published more than 20 papers on many international famous journals.
URL:https://www.fst.um.edu.mo/event/pointwise-error-estimates-of-the-novel-nonlinear-fourth-order-compact-difference-scheme-for-viscous-burgers-equation/
LOCATION:E11-1006
CATEGORIES:event_list,math_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210702T160000
DTEND;TZID=Asia/Macau:20210702T170000
DTSTAMP:20260612T054412
CREATED:20210629T094053Z
LAST-MODIFIED:20220927T033405Z
UID:17574-1625241600-1625245200@www.fst.um.edu.mo
SUMMARY:SKL-IOTSC Talk Series: On the Dynamics of the South China Sea Circulation智慧城市物聯網系列講座: 南海環流動力過程
DESCRIPTION:科技學院教授獲邀在智慧城市物聯網系列講座上分享相關領域的專業知識\, 蔡忠亞助理教授將分享南海環流動力過程的知識 \n日期Date: 2021.07.2 (Friday)\n時間Time: 16:00 – 17:00\n地點Venue: N21 5樓展覽廳 N21-5/F EXHIBITION HALL\n語言Language: 英語English \n\n人物簡介:  \n蔡忠亞教授剛於2020年加入澳大並在科技學院土木及環境工程系擔任助理教授，同時也作為智慧城市物聯網國家重點實驗室及區域海洋研究中心的研究成員之一。蔡教授過去在中國海洋大學獲得本科和碩士學位，這是一所以研究海洋和水產學科聞名的大學。及後，他在香港科技大學完成海洋環境科學博士學位，研究領域包括海水流動、海洋環境生態、南海的多尺度環流與動力學。其中蔡教授更善長數值模擬，在設計好的模型中輸入數據，觀察並分析結果。\nProf. Cai Zhongya has joined UM in 2020 as an Assistant Professor in the Department of CEE. He is also one of the research members of SKL-IOTSC and the Centre for Regional Oceans. Prof. Cai obtained his bachelor and master degrees in Ocean University of China\, which is an university well-known for studying marine and aquatic subjects. Afterwards\, he completed his PhD degree in Marine Environmental Sciences at the Hong Kong University of Science and Technology. His research areas include seawater flow\, marine environmental ecology\, and multi-scale circulation and dynamics in the South China Sea. Among them\, Prof. Cai is better at numerical simulation\, inputting data into the designed model\, observing and analyzing the results. \n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 
URL:https://www.fst.um.edu.mo/event/skl-iotsc-talk-series-on-the-dynamics-of-the-south-china-sea-circulation/
LOCATION:N21- 5/F Exhibition Hall
CATEGORIES:cee_events,event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210702T170000
DTEND;TZID=Asia/Macau:20210702T180000
DTSTAMP:20260612T054412
CREATED:20210629T094613Z
LAST-MODIFIED:20220927T033405Z
UID:17575-1625245200-1625248800@www.fst.um.edu.mo
SUMMARY:SKL-IOTSC Talk Series: From Power Quality to Cyber Attack: Cyber-physical 智慧城市物聯網系列: 能源物聯網的信息物理安全研究
DESCRIPTION:科技學院教授獲邀在智慧城市物聯網系列講座上分享相關領域的專業知識\, 劉景榮助理教授將分享能源物聯網的信息物理安全研究的知識\n\n\n\n\n\n日期Date: 2021.07.2 (Friday)\n時間Time: 17:00 – 18:00\n地點Venue: N21 5樓展覽廳 N21-5/F EXHIBITION HALL\n語言Language: 英語English \n\n人物簡介: \n劉景榮教授現任電腦及電機工程系助理教授以及智慧城市物聯網國家重點實驗室（IOTSC）成員之一。 2016年在澳大獲取電腦及電機工程系博士學位後，曾任德克薩斯大學奧斯汀分校的研究學者。 2017 年 6 月至 2019 年 6 月在美國從事電能質量、智能電網、能源物聯網以及網絡物理安全方面的研究，並發表了 30 多篇國際期刊和會議文章。 \nProf. Lao is currently an assistant professor with the Department of Electrical and Computer Engineering\, as well as the State Key Laboratory of Internet of Things for Smart City (IOTSC). He graduated from UM and was  a research scholar at the University of Texas at Austin. USA from June 2017 to June 2019. He has been conducting research on power quality\, smart grid\, energy internet of things\, as well as cyber-physical security and has published more than 30 International journal transactions and conferences.
URL:https://www.fst.um.edu.mo/event/skl-iotsc-talk-series-from-power-quality-to-cyber-attack-cyber-physical/
LOCATION:N21- 5/F Exhibition Hall
CATEGORIES:ece_events,event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210705T103000
DTEND;TZID=Asia/Macau:20210705T113000
DTSTAMP:20260612T054412
CREATED:20210629T040046Z
LAST-MODIFIED:20220927T033405Z
UID:17567-1625481000-1625484600@www.fst.um.edu.mo
SUMMARY:Wilks’ Theorems in Some Random Graph Models
DESCRIPTION:Instructors/Speakers\nProf. Ting YAN\nProfessor\nHuazhong Normal University\nChina \nAbstract\nIn this talk\, we will show Wilks’ theorems in two random graph models—the beta model and the Bradley-Terry model. For fixed dimensional parameter testing problems\, we show that minus twice log-likelihood ratio statistics in the null converge to the Chi-square distribution although the number of nuisance parameters goes to infinity. For increasing dimensional parameter testing problem\, we reveal high dimensional Wilks phenomenon.\n \nBiography\nProf. Ting YAN obtained his Ph.D. degree in University of Science and Technology of China in 2012\, works as a full professor at Huazhong Normal University. His main research interests include Network models\, Random Graphs\, Paired comparisons\, etc. His research has been supported by three projects of National Natural Science Foundation of China\, and he has published more than 30 journal papers\, including several top journals in Statistics\, such as Annals of Statistics\, Biometrika and Journal of the American Statistical Association.
URL:https://www.fst.um.edu.mo/event/wilks-theorems-in-some-random-graph-models/
LOCATION:E11-1006
CATEGORIES:event_list,math_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210707T160000
DTEND;TZID=Asia/Macau:20210707T170000
DTSTAMP:20260612T054412
CREATED:20210705T072714Z
LAST-MODIFIED:20220927T033404Z
UID:17759-1625673600-1625677200@www.fst.um.edu.mo
SUMMARY:SKL-IOTSC Talk Series: Electric Energy Router and its Technologies智慧城市物聯網系列講座: 電能路由器及其相關技術
DESCRIPTION:科技學院教授獲邀在智慧城市物聯網系列講座上分享相關領域的專業知識\, 黃民聰教授將分享電能路由器及其相關技術的知識 \n日期Date: 2021.07.7 (Wednesday)\n時間Time: 16:00 – 17:00\n地點Venue: N21 5樓展覽廳 N21-5/F EXHIBITION HALL\n語言Language: 英語English \n\n人物簡介:  \n黃民聰教授於1993年加入澳大，現已是電機及電腦工程系正教授，同時也作為智慧城市物聯網國家重點實驗室的研究成員之一。黃教授2003年在清華大學獲得電機及電腦工程博士學位，1997及1993年在澳大獲碩士及本科學位，他的研究領域包括電力電子、電源系統、儀器儀表和測量、智能電網、有源電源濾波器、綜合電源及能源物聯網 \nProf. Man Chung Wong joined UM in 1993\, now he is a Professor in the Department of ECE. He is also one of the research members of SKL-IOTSC. Prof. Wong obtained his PhD degree in Tsinghua University in 2003 and his master and bachelor degrees from UM in 1997 and 1993. His research areas include Power Electronics\, Power System\, Instrumentation and Measurement\, Smart Grid\, Active Power Filter\, Integrated Power and Energy IOT.
URL:https://www.fst.um.edu.mo/event/skl-iotsc-talk-series-electric-energy-router-and-its-technologies/
LOCATION:N21- 5/F Exhibition Hall
CATEGORIES:ece_events,event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20210920T100000
DTEND;TZID=Asia/Macau:20210920T110000
DTSTAMP:20260612T054412
CREATED:20210917T093737Z
LAST-MODIFIED:20220927T033257Z
UID:19139-1632132000-1632135600@www.fst.um.edu.mo
SUMMARY:Teissier problem for nef classes
DESCRIPTION:Instructors/Speakers\nProf. Yashan Zhang\nAssociate Professor\nHunan University\nChina \nAbstract\nTeissier problem aims to characterize the equality case of Khovanskii-Teissier type inequality for (1\,1)-classes on a compact Kaehler manifold. When each of the involved (1\,1)-classes is assumed to be nef and big\, this problem has been solved by the previous works of Boucksom-Favre-Jonsson\, Fu-Xiao and Li. In this talk\, we shall introduce our recent work which settles the case that the involved (1\,1)-classes are just assumed to be nef. By constructing examples\, it is shown that our results are optimal.\n \nBiography\nProf. Yashan Zhang obtained his Ph.D. degree in University of Macau in 2017\, works as an associate professor at Hunan University\, Changsha. His main research interests include Complex Geometry\, Geometric Analysis\, etc.
URL:https://www.fst.um.edu.mo/event/teissier-problem-for-nef-classes/
LOCATION:E11-1035
CATEGORIES:event_list,math_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20211205
DTEND;VALUE=DATE:20211208
DTSTAMP:20260612T054412
CREATED:20211124T075838Z
LAST-MODIFIED:20220927T033256Z
UID:19587-1638662400-1638921599@www.fst.um.edu.mo
SUMMARY:Celebrating the 40th Anniversary of the University of Macau: The 3rd International Conference on High  Performance Big Data and Intelligent Systems (HPBD&IS) and 2021 Macao Symposium on Cloud Computing and  Intelligent Driving (CCID) 國際高性能大數據與智能系統國際會議暨澳門首屆雲計算與智能駕駛研討會
DESCRIPTION:Celebrating the 40th Anniversary of the University of Macau: \nThe 3rd International Conference on High Performance Big Data and Intelligent Systems (HBPD & IS) and 2021 Macao Symposium on Cloud Computing and Intelligent Driving (CCID)\n國際高性能大數據與智能系統國際會議暨澳門首屆雲計算與智能駕駛研討會\nDate: 5-7 December 2021\nTime: 5-6 Dec 9:00-18:00\, 7 Dec 9:00-12:30\nVenue: N1 Banquet Hall\, University of Macau
URL:https://www.fst.um.edu.mo/event/the-3rd-international-conference-on-high-performance-big-data-and-intelligent-systems-hbpdis-and-2021-macao-symposium-on-cloud-computing-and-intelligent-driving-ccid/
LOCATION:N1-Banquet Hall\, University of Macau
CATEGORIES:conferences,event_list,seminarslectures
END:VEVENT
END:VCALENDAR