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DTSTART:20190101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190814T094500
DTEND;TZID=Asia/Macau:20190814T103000
DTSTAMP:20260612T041940
CREATED:20190814T014539Z
LAST-MODIFIED:20220927T042353Z
UID:5866-1565775900-1565778600@www.fst.um.edu.mo
SUMMARY:Learning to Build a New Reality
DESCRIPTION:Instructors/Speakers\nProf. Jingyi YU\nShanghaiTech University\nChina \nAbstract\nThere have been tremendous advances on applying deep learning techniques for 2d image understanding. In contrast\, very little work has focused on employing deep learning for modeling datasets beyond 2D such as 3D geometry and 4D light fields. In this talk\, I present several latest works from our group on in this exciting new arena\, with a focus on their applications to virtual and augmented reality and computational photography. I first present a novel deep surface light field (DSLF) technique. A surface light field represents the radiance of rays originating from any points on the surface in any directions. Traditional approaches require ultra-dense sampling to ensure the rendering quality. Our DSLF works on sparse data and automatically filling in the missing data by leveraging different sampling patterns across the vertices and at the same time eliminates redundancies due to the network’s prediction capability. For real data\, we address the image registration problem as well as conduct texture-aware remeshing for aligning texture edges with vertices to avoid blurring. Next\, I present an end-to-end deep learning scheme to establish dense shape correspondences and subsequently compress 3d dynamic human bodies. Our approach uses sparse set of “panoramic” depth maps or PDMs\, each emulating an inward-viewing concentric mosaics (CM). We then develop a learning-based technique to learn pixel-wise feature descriptors on PDMs. The results are fed into an autoencoder-based network to achieve ultra-high compression ratio. \nBiography\nJingyi Yu is currently a Full Professor and Associate Dean of the School of Information Science and Technology at ShanghaiTech University. He is also affiliated with the Department of Computer and Information Sciences at University of Delaware. He received B.S. from Caltech in 2000 and Ph.D. from MIT in 2005. He has published over 120 papers at highly refereed conferences and journals\, and holds over 10 international patents on computational imaging. His research interests span a range of topics in computer vision and computer graphics\, especially on computational photography and non-conventional optics and camera designs. He is a recipient of the NSF CAREER Award and the AFOSR YIP Award\, and has served as an area chair of many international conferences including CVPR\, ICCV\, ECCV\, ICCP and NIPS. He is currently an Associate Editor of IEEE TPAMI\, IEEE TIP\, and Elsevier CVIU\, and will be program chair of ICPR 2020 and IEEE CVPR 2021. \n 
URL:https://www.fst.um.edu.mo/event/learning-to-build-a-new-reality/
LOCATION:E11-G015 (University of Macau)
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190814T103000
DTEND;TZID=Asia/Macau:20190814T111500
DTSTAMP:20260612T041940
CREATED:20190814T023011Z
LAST-MODIFIED:20220927T042352Z
UID:5862-1565778600-1565781300@www.fst.um.edu.mo
SUMMARY:Towards Intelligent Perception of Facial Images from End to End
DESCRIPTION:Instructors/Speakers\nProf. Junliang XING\nInstitute of Automation\, Chinese Academy of Sciences\nChina \nAbstract\nFace is perhaps the most important visual object in computer vision\, with extensive studies in the past decades. In the deep learning era\, the performances of computer vision problems related to faces have been significantly boosted\, many of which have already met the requirements in real-world applications. In the talk\, I will first make some basic introductions on the face vision problems\, including face detection\, face alignment\, face tracking\, face attribute analyses and face recognition. Then I will introduce some of our previous works related to this topic. At last\, I will point out some future trends in this direction. The main objective of this talk is to help the audiences get a comprehensive understanding of this relatively mature yet still hot research direction in computer vision. \nBiography\nDr. Junliang XING received his dual B.E. degrees in Computer Science and Applied Mathematics from Xi’an Jiaotong University\, 2007\, and his Ph.D. degree in Computer Science and Technology from Tsinghua University\, 2012. After that\, he became an assistant professor within the National Laboratory of Pattern Recognition\, Institute of Automation\, Chinese Academy of Sciences\, where he is now a Professor and master student supervisor. Dr. Xing has published over 100 papers in peer-reviewed international conferences like ICCV\, CVPR\, ECCV\, ACM Multimedia\, AAAI\, IJCAI\, and journals like TPAMI\, IJCV\, TIP\, PR. He has translated two books in computer vision and wrote one book on deep learning. Dr. Xing was the recipient of Google PhD Fellowship in 2011\, the Best Paper Award of ACM International Conference on Multimedia in 2013\, and the champions of many international AI technical competitions in face recognition\, pose estimation\, etc. His main research areas lie in pattern recognition\, computer vision\, and machine learning\, with a main focus on vision problems related to human faces and bodies. \n 
URL:https://www.fst.um.edu.mo/event/towards-intelligent-perception-of-facial-images-from-end-to-end/
LOCATION:E11-G015 (University of Macau)
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190814T103000
DTEND;TZID=Asia/Macau:20190814T113000
DTSTAMP:20260612T041940
CREATED:20190814T023049Z
LAST-MODIFIED:20220927T042352Z
UID:5864-1565778600-1565782200@www.fst.um.edu.mo
SUMMARY:Error convolution structure in discrete Caputo derivatives and global consistency analysis
DESCRIPTION:Instructors/Speakers\nProf. Jiwei ZHANG\nSchool of Mathematics and Statistics\nWuhan University\nChina \nAbstract\nNonuniform time-stepping methods are promising for Caputo reaction sub-diffusion problems because they would be simple and effectiveness in resolving the initial singularity and other nonlinear behaviors occurred away from the initial time. Compared with traditional local methods for the first-order derivative\, the numerical analysis for nonlocal time-stepping schemes on non-uniform time meshes are challenging due to the convolution integral (nonlocal) form of fractional derivative. We develop a general framework for the stability and convergence analysis with three tools: a family of complementary discrete convolution kernels\, a discrete fractional Gronwall inequality (DFGI) and a global (convolutional) consistency analysis\, which is not limited to a specific time mesh by building a convolution structure of local truncation error. It seems that the present techniques are extendable to the variable-order\, distributed-order diffusion equations and other nonlocal-in-time diffusion problems. \nBiography\nProf Zhang is a Professor of School of Mathematics and Statistics\, Wuhan University. He got his PhD degree in Hong Kong Baptist University in 2009. His research area include fast algorithms for fractional PEDs and numerical methods for PDEs. \n 
URL:https://www.fst.um.edu.mo/event/error-convolution-structure-in-discrete-caputo-derivatives-and-global-consistency-analysis/
LOCATION:E11-1006
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190814T111500
DTEND;TZID=Asia/Macau:20190814T120000
DTSTAMP:20260612T041940
CREATED:20190814T031550Z
LAST-MODIFIED:20220927T042352Z
UID:5859-1565781300-1565784000@www.fst.um.edu.mo
SUMMARY:Multi-View Fusion and Representation for Image Analysis
DESCRIPTION:Instructors/Speakers\nProf. Zhe XUE\nBeijing University of Posts and Telecommunications\nChina \nAbstract\nReal-world data can be described from multiple views. For instance\, an image can be described by color histogram\, SIFT\, HOG and other features. The content of a Web page can be described by texts\, images and videos. Describing an object from multiple perspectives constitutes multi-view data. Multi-view learning is to use the complementary nature of different views to improve the learning performance than using a single view. In this talk\, I will first briefly introduce some basic concepts and issues in multi-view learning. Then I will introduce some of our recent multi-view learning works for image analysis including multi-view dimensionality reduction\, multi-view clustering and incomplete multi-view classification. This report aims to help the audience understand the basic tasks and latest developments of multi-view learning. \nBiography\nDr. Zhe Xue received his Ph\,D. degree in Computer Science from school of computer and control engineering\, University of Chinese Academy of Sciences (UCAS) in 2017. After that\, he became an assistant professor at school of computer science\, Beijing University of Posts and Telecommunications. His research interest is generally in machine learning and data mining\, and particularly in multi-view learning and image analysis. Dr. Xue has published over 20 papers in international conferences and journals such as AAAI\, IJCAI\, IEEE TCSVT\, CVIU\, Information Sciences. He has undertook and participated in many projects\, including National Key R&D Program of China\, 973 Program\, National Natural Science Foundation of China and so on. He is the reviewer of ACM MM\, DASFAA\, IEEE TIFS\, Multimedia Tools and Applications and other international journals and conferences. He is also a member of the Intelligent Service Committee of the Chinese Association for Artificial Intelligence. \n 
URL:https://www.fst.um.edu.mo/event/multi-view-fusion-and-representation-for-image-analysis/
LOCATION:E11-G015 (University of Macau)
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190814T151500
DTEND;TZID=Asia/Macau:20190814T160000
DTSTAMP:20260612T041940
CREATED:20190814T071525Z
LAST-MODIFIED:20220927T042351Z
UID:5854-1565795700-1565798400@www.fst.um.edu.mo
SUMMARY:Integrating Learning with Game Theory for Societal Challenges
DESCRIPTION:Instructors/Speakers\nProf. Fei Fang\nInstitute for Software Research\nSchool of Computer Science\nCarnegie Mellon University\nUSA \nAbstract\nThere is a rising interest in developing artificial intelligence-based tools to help address societal challenges. Motivated by these challenges\, we have proposed game theory and machine learning/reinforcement learning-based models and algorithms for problems with strategic interactions among agents. In this talk\, I will introduce our models and algorithms that have led to two successfully deploy applications: one used by US Coast Guard for protecting the Staten Island Ferry in New York City since April 2013\, the other used in multiple conservation areas around the world for anti-poaching effort. In addition\, I will highlight our most recent advances in integrating deep learning with game theory\, including computing equilibrium by learning from self-play and end-to-end learning of game parameters. \nBiography\nFei Fang is an Assistant Professor at the Institute for Software Research in the School of Computer Science at Carnegie Mellon University. Before joining CMU\, she was a Postdoctoral Fellow at the Center for Research on Computation and Society (CRCS) at Harvard University. She received her Ph.D. from the Department of Computer Science at the University of Southern California in June 2016. She received her bachelor degree from the Department of Electronic Engineering\, Tsinghua University in July 2011. Her research lies in the field of artificial intelligence and multi-agent systems\, focusing on integrating game theory and mechanism design with machine learning. Her work has been motivated by and applied to security\, sustainability\, and mobility domains\, contributing to the theme of AI for Social Good. Her work has won the Distinguished Paper at the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI’18)\, Innovative Application Award at Innovative Applications of Artificial Intelligence (IAAI’16)\, the Outstanding Paper Award in Computational Sustainability Track at the International Joint Conferences on Artificial Intelligence (IJCAI’15). Her dissertation is selected as the runner-up for IFAAMAS-16 Victor Lesser Distinguished Dissertation Award\, and is selected to be the winner of the William F. Ballhaus\, Jr. Prize for Excellence in Graduate Engineering Research as well as the Best Dissertation Award in Computer Science at the University of Southern California. Her work has been deployed by the US Coast Guard for protecting the Staten Island Ferry in New York City since April 2013. Her work has led to the deployment of PAWS (Protection Assistant for Wildlife Security) in multiple conservation areas around the world\, which provides predictive and prescriptive analysis for anti-poaching effort. \n 
URL:https://www.fst.um.edu.mo/event/integrating-learning-with-game-theory-for-societal-challenges/
LOCATION:N1-1004\, Centre for Innovation and Entrepreneurship\, Guest House\, University of Macau
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190816T111500
DTEND;TZID=Asia/Macau:20190816T121500
DTSTAMP:20260612T041940
CREATED:20190816T031526Z
LAST-MODIFIED:20220927T040651Z
UID:5852-1565954100-1565957700@www.fst.um.edu.mo
SUMMARY:Gap probability in critical random matrix ensembles and the coupled Painleve II system
DESCRIPTION:Instructors/Speakers\nDr. Shuai-Xia XU\nLecturer\nSun Yat-sen University\nChina \nAbstract\nWe study the gap probabilities in the critical unitary invariant random matrix ensembles\, where the Painleve II and Painleve XXXIV kernels arise. By studying the Fredholm determinants of the Painleve II and Painlev XXXIV kernels\, we obtain integral expression of the gap probabilities by using solutions to the coupled Painleve II system. Moreover\, the large gap asymptotics are derived with the constant terms given explicitly in terms of the Riemann zeta-function. This talk is based on a joint work with Dan Dai from City University of HongKong. \nBiography\nProf. Xu Shuaixia got his PhD degree from Sun Yat-sen University in 2011. From 2011 to 2013\, he worked as a postdoctoral fellow at Sun Yat-sen and is currently a lecturer at Sun Yat-sen University. His research areas include nuclear science and technology-other disciplines of nuclear science and technology. \n 
URL:https://www.fst.um.edu.mo/event/gap-probability-in-critical-random-matrix-ensembles-and-the-coupled-painleve-ii-system/
LOCATION:E11-1006
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190909T103000
DTEND;TZID=Asia/Macau:20190909T233000
DTSTAMP:20260612T041940
CREATED:20190909T023011Z
LAST-MODIFIED:20220927T040651Z
UID:5849-1568025000-1568071800@www.fst.um.edu.mo
SUMMARY:History of the Generalized Inverse & Linear Least Squares
DESCRIPTION:Instructors/Speakers\nProf. Yimin WEI\nProfessor\nSchool of Mathematical Sciences\nFudan University\nChina \nAbstract\nIn this talk\, we will introduce the history of the generalized inverse and linear least squares problem. Some recent research in this area will be given. Possible future work will also be discussed. \nBiography\nProf. Yimin WEI is a professor in Fudan University\, China. He has published over 100 papers in mathematics. His recent interest includes matrix analysis\, least squares problems and study of multilinear systems. \n 
URL:https://www.fst.um.edu.mo/event/history-of-the-generalized-inverse-linear-least-squares/
LOCATION:E11-1035
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190911T143000
DTEND;TZID=Asia/Macau:20190911T153000
DTSTAMP:20260612T041940
CREATED:20190911T063058Z
LAST-MODIFIED:20220927T040650Z
UID:5823-1568212200-1568215800@www.fst.um.edu.mo
SUMMARY:Security design of IoT products
DESCRIPTION:Instructors/Speakers\nMr. Zexin JIANG\nGuangzhou Bonson Information System Co. Ltd. \nAbstract\n\n簡單自我介紹\n\n平凡的我出生在不平凡的地方\n不吃辣椒，卻孤身一路向北\n明明可以安穩舒適，卻非要折騰\n\n\n大四之後的求學\n\n沒有畢業合照的大四\n我是如何保送到清華進修的\n國家高鐵系統真的運行著我寫的代碼嗎\n深深地遺憾\n\n\n職場折騰\n\n內地壟斷國企是一種什麼樣的存在\n獨檔一面是一種什麼樣的感受\n如何避免當背鍋俠\n我在電網工作5年獲得的5個第一\n辭職之後我拿著兩份工資\n民企與國企的差異極大\n一年時間從產品經理到CTO\n技術、產品、工程有什麼區別，變現的誤區\n\n\n幾點感悟分享\n\n選擇比努力重要\n多做事少計較得失\n適當包裝自己\n風險管理與自我保護\n\n\n\nBiography\n廣東省普寧人，高級工程師职称，（ISC）2會員、全國電力運行與控制標準委員會標準工作組成員、廣東省電機工程學會成員、廣州市科技評審專家，獲得國家授權專利56項，發表論文12篇，出版專著1本，獲省級科技進步壹等獎、獲2018年廣州市“珠江科技新星”專項資助、2019年廣州市“產業急需緊缺人才”補貼。擁有國際註冊信息安全專家和國家重要信息系統保護人員等職業資格。 \n2004年-2008年，南京理工大學自動化專業本科學習（專業第1名，GPA 3.9/4.0）。參加全國大學生電子設計大賽獲國家二等獎、全國大學生智能汽車比賽獲得國家二等獎、江蘇省大學生機器人比賽獲得壹等獎、江蘇省優秀本科畢業論文壹等獎、獲得學校最高榮譽獎學金以及每年特等獎學金。 \n2008年-2011年，清華大學（免試）控制科學與工程專業碩士研究生。期間參與“十壹五”國家重大科技攻關（中國高鐵國產化裝備研發）項目以及和諧號CRH5動車組網絡控制系統的引進消化吸收創新的產品研發工作。研發了支持硬件在環的大規模分布式半實物仿真引擎，研發成果支撐應用於武廣、京津、北京地鐵等線路設備的上線前驗證。 \n2011年至2016年，廣東電網電力科學研究院（南方電網自動化重點實驗室），歷任助理專責、專責、技術專家、電力機器人攻關團隊組長。從事電力物聯網和電力監控安全防護體系領域的研究工作，主筆編制了南方電網電力監控系統最頂層安全防護技術規範和管理規範等多項企業標準，參與電力行業信息安全標準編制2項，推動商用密碼技術在電力行業的應用，相關成果於2012年獲得廣東省電力行業協會科技創新成果獎、於2013年南方電網青工創新創效成果壹等獎、2014年獲得南方電網科技進步壹等獎。2015年在南方電網全網信息安全攻防競賽獲第1名。 \n2016年至今，廣州邦訊信息系統有限公司（深交所股票代碼：300366），歷任產品經理、產品副總監、CTO。主要從事工業物聯網和物聯網安全相關產品研發管理工作。創建了公司商用密碼產品線，帶領團隊研發多款物聯網及安全產品，獲得國家密碼局型號認證和公安部檢測認證。 \n 
URL:https://www.fst.um.edu.mo/event/security-design-of-iot-products/
LOCATION:E11-1006 (University of Macau)
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190911T150000
DTEND;TZID=Asia/Macau:20190911T160000
DTSTAMP:20260612T041940
CREATED:20190911T070002Z
LAST-MODIFIED:20220927T040650Z
UID:5814-1568214000-1568217600@www.fst.um.edu.mo
SUMMARY:Image Authentication and Tamper Localization
DESCRIPTION:Instructors/Speakers\nProf. Yulin WANG\nFull Professor of Wuhan University\nChina \nAbstract\nImage authentication can be used in many fields\, including e-government\, e-commerce\, national security\, news pictures\, court evidence\, medical image\, engineering design\, and so on. Since some content-preserving manipulations\, such as JPEG compression\, contrast enhancement\, and brightness adjustment\, are often acceptable—or even desired—in practical application\, an authentication method needs to be able to distinguish them from malicious tampering\, such as removal\, addition\, and modification of objects. Therefore\, the traditional hash-based authentication is not suitable for the application. As for the semi-fragile watermarking technique\, it meets the requirements of the above application at the expense of severely damaging image fidelity. In this talk\, we propose a hybrid authentication technique based on what we call fragile hash value. The technique can blindly detect and localize malicious tampering\, while maintaining reasonable tolerance to conventional content-preserving manipulations. The hash value is derived from the relative difference between each pair of the selected DCT coefficient in a central block and its counterpart which is estimated by the DC values of the center block and its adjacent blocks. In order to maintain the relative difference relationship when the image undergoes legitimate processing\, we make a pre-compensation for the coefficients. Finally\, we point out the direction using deep leaning technique for image authentication. \nBiography\nProf. Yulin Wang is a full professor and PhD supervisor in the School of Computer Science\, Wuhan University\, China. He got PhD degree in 2005 from University of London\, UK. Before that\, he had worked in National Institute of Research and Huawei@ for more than ten years. He has involved more than 20 national and international research projects\, and hold 8 patents. He got his master and bachelor degree in 1990 and 1987 respectively from Xi-Dian University\, and Huazhong University of Science and Technology\, both in China. His research interests include image and video processing\, software engineering\, information security and artificial intelligence. In recently 10 years\, Prof. Wang has published as first author 3 books\, 40 conference papers and 45 journal papers\, including in IEEE Transactions and ACM Transactions journals. Prof. Wang served as editor-in-chief for International Journal of Advances in Multimedia in 2010. He served as reviewer for many journals\, including IEEE Transactions on Image Processing\, IEEE Transactions on CSVP and IEEE Transactions on Multimedia. He served as reviewer for many research funds\, including National High Technology Research and Development Program of China (‘863’ project). Prof. Wang was the external PhD adviser of Dublin City University\, Ireland during 2013-2016. He has served as chairman and keynote speaker at more than 30 international conferences since 2008. He bas been listed in Marcus “who’s who in the world” since 2008. He was selected as scientific and technological innovative talents in Hubei Province in 2014. Since 2012\, he has served as Deputy Director of Hubei Science and Technology Commission of China Association for the Promotion of Democracy (CAPD). \n 
URL:https://www.fst.um.edu.mo/event/image-authentication-and-tamper-localization/
LOCATION:E11-4045
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190919T143000
DTEND;TZID=Asia/Macau:20190919T153000
DTSTAMP:20260612T041940
CREATED:20190919T063006Z
LAST-MODIFIED:20220927T040650Z
UID:5801-1568903400-1568907000@www.fst.um.edu.mo
SUMMARY:Sinotools: a computational framework to analyze cancer genomic sequencing data for precision oncology
DESCRIPTION:Instructors/Speakers\nProf. Bingding HUANG\nCollege of Big Data and Internet\nShenzhen University \nAbstract\nWe have developed a computational framework called Sinotools to analyze cancer genomic sequencing data for precision oncology. First of all\, Sinotools can identify very low-frequency variants in ctDNA samples from cancer patients using duplex barcode sequencing technology. Sinotools also includes a novel computational algorithm to identify actionable gene fusion events from targeted sequencing data. Sinotools is available at https://github.com/SinOncology. \nBiography\nProf. Bingding Huang received his BSc in Cell Biology from University of Science and Technology of China in 2002. Then he received his Master degree in Computer Science from Saarland University and Max Planck Institute for Informatics under Scholarship from International Max Planck Research School in 2004. Afterwards\, he joined the Bioinformatics group in Technical University of Dresden where he received his PhD (Dr.ret.nat) in Computer Science from the Computer Science department in 2007. Then he joined the Molecular and Cellular Modeling group in Heidelberg Institute for Theoretical Studies for one year postdoc training. From 2009 to 2012 he was a Adjunct Associate Professor in Division of Systems Biology\, Zhejiang-California International NanoSystems Institute\, Zhejiang University China. From 2012 to 2015 Dr. Huang worked as a Bioinformatics Scientist in German Cancer Research Center Heidelberg. Then from 2015 to 2017 he worked as a Senior Computational Biologist in Neo New Oncology AG (Part of Siemens Healthineers). Afterwards\, he joined Sinotech Genomics Inc. Shanghai as Vice President of Research and Development and Head of Bioinformatics. Recently Dr. Huang joined the College of Big Data and Internet\, Shenzhen University as a full Professor in Bioinformatics and Big data. \n 
URL:https://www.fst.um.edu.mo/event/sinotools-a-computational-framework-to-analyze-cancer-genomic-sequencing-data-for-precision-oncology/
LOCATION:E12-G004
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190923T150000
DTEND;TZID=Asia/Macau:20190923T160000
DTSTAMP:20260612T041940
CREATED:20190923T070040Z
LAST-MODIFIED:20220927T040649Z
UID:5796-1569250800-1569254400@www.fst.um.edu.mo
SUMMARY:Exploring Deep Learning from Feedforward Neural Network Experiments
DESCRIPTION:Instructors/Speakers\nProf. Qin SHENG\nProfessor\nDepartment of Mathematics\nBaylor University\nUSA \nAbstract\nNeural network based deep learnings have been used for solving high dimensional (number of dimensions may reach more than several hundreds) partial differential equations. But what is a neural network and how to use it for approximating\, or predicting\, natural phenomena? In this exploration\, we tend to consider approximations of multivariate data through an explicit feedforward neural network (FNN) which is the basic type of neural network. The easy-to-follow formula provides a piecewise constant function for the data. Our FNN architecture has two hidden layers\, where the weights and thresholds are explicitly defined and no numerical optimization is required for training. The explicit algorithm does not rely on any tensor structure in multiple dimensions. Instead\, it automatically creates Voronoi tessellation of the domain based on the given data\, and generates a reliable piecewise constant approximation of the targeted function. These make the construction more practical for multiple applications. \nBiography\nProf. Sheng is a professor of Department of Mathematics\, Baylor University\, USA. He got his PhD degree from the University of Cambridge under the supervision of Professor Arieh Iserles in 1990. His research area include splitting and adaptive numerical methods for solving linear and nonlinear partial differential equations. \n 
URL:https://www.fst.um.edu.mo/event/exploring-deep-learning-from-feedforward-neural-network-experiments/
LOCATION:E11-1006
CATEGORIES:event_list,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190925T100000
DTEND;TZID=Asia/Macau:20190925T110000
DTSTAMP:20260612T041940
CREATED:20190925T091150Z
LAST-MODIFIED:20220927T040649Z
UID:5792-1569405600-1569409200@www.fst.um.edu.mo
SUMMARY:Summability and Lebesgue points of two-dimensional Fourier transforms
DESCRIPTION:Instructors/Speakers\nProf. Weisz FERENC\nProfessor\nDepartment of Numerical Analysis\nEötvös L. University\nHungary \nAbstract\n \nBiography\nProfessor Ferenc Weisz works for Eötvös Loránd University\, Department of Numerical Analysis\, Budapest\, Hungary\, Europe. His special field is harmonic analysis\, one and higher dimensional Fourier analysis\, summability theory\, martingale theory\, Hardy spaces\, spaces with variable exponents\, Gabor- and wavelet analysis. He is author of four books published by Springer and Birkhäuser\, two course books and of about 200 papers published by international journals. He has got several prizes and awards\, amongst other in the last two years the Gabor prize and teh Prize of the Hungarian Academy of Sciences. He has got the Doctor of Science (DSc) degrree of the Hungarian Academy of Sciences in 2001 and the Habilitation of the Eötvös Loránd University\, Budapest in 2002. \n 
URL:https://www.fst.um.edu.mo/event/summability-and-lebesgue-points-of-two-dimensional-fourier-transforms/
LOCATION:E11-1015
CATEGORIES:event_list,math_events,seminarslectures
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Macau:20190925T110000
DTEND;TZID=Asia/Macau:20190925T120000
DTSTAMP:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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:20260612T041940
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
END:VCALENDAR