Qingfu Zhang (张青富), City University of Hong Kong, Hong Kong, China
张青富教授现为香港城市大学电脑科学系计算智能讲座教授、长江学者讲座教授、IEEE Fellow。2016至2020连续入选Web of Science计算机科学领域的高被引学者，总引用超过两万次。主要从事智能计算、多目标优化及机器学习方面的研究。他提出的多目标分解算法框架MOEA/D已成为目前多目标进化计算领域最常用的两种框架之一。
Qingfu Zhang is a Professor at the Department of Computer Science, City University of Hong Kong. His main research interests include evolutionary computation, optimization, neural networks, data analysis, and their applications. His MOEA/D has been one of most researched and used multiobjective evolutionary algorithmic framework. He is currently leading the Metaheuristic Optimization Research Group in City University of Hong Kong. Professor Zhang is an Associate Editor of the IEEE Transactions on Evolutionary Computation and the IEEE Transactions Cybernetics. He was awarded the 2010 IEEE Transactions on Evolutionary Computation Outstanding Paper Award. He is on the list of the Thomson Reuters 2016 highly cited researchers in computer science. He is a fellow of IEEE
Speech Title: Introduction to Decomposition Based Multiobjective Optimization
Xiao Wu, Southwest Jiaotong University, China
Prof. Xiao Wu is a full Professor and the Assistant Dean of School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China. He received the B.Eng. and M.S. degrees in computer science from Yunnan University, Yunnan, China, in 1999 and 2002, respectively, and the Ph.D. degree in Computer Science from City University of Hong Kong, Hong Kong in 2008. He was with the Institute of Software, Chinese Academy of Sciences, Beijing, China, from 2001 to 2002. He was a Research Assistant and a Senior Research Associate at the City University of Hong Kong, Hong Kong, from 2003 to 2004, and 2007 to 2009, respectively. He was with the School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA, and at School of Information and Computer Science, University of California, Irvine, CA, USA as a Visiting Scholar during 2006 to 2007 and 2015 to 2016, respectively. He has authored or co-authored more than 70 research papers in well-respected journals, such as TIP, TMM, TMI, TITS and prestigious proceedings like CVPR, ICCV and ACM MM. He received the Second Prize of Natural Science Award of the Ministry of Education, China in 2016 and the Second Prize of Science and Technology Progress Award of Henan Province, China in 2017. His research interests include artificial intelligence, computer vision, multimedia information retrieval, and image/video computing.
Speech Title: Exploration of Deep Learning for Fashion Search and Recommendation
Abstract: With the exponential growth of e-commerce, online clothing shopping becomes more and more popular, which takes up a significant portion of the retail. Driven by the huge profit potential, clothing item retrieval has been received a great deal of attention in multimedia and computer vision communities. Meanwhile, deep learning has shown its promising ability in many fields of computer science, such as computer vision, natural language processing and multimedia. In this talk, we will push the frontier of fashion search and recommendation by bringing together techniques from computer vision and deep learning. We seeks to advance fashion studies and techniques, including fashion search, clothing image generation and fashion recommendation.
Huaiyu Dai, NC State University, USA
Huaiyu Dai (F’17) received the B.E. and M.S. degrees in electrical engineering from Tsinghua University, Beijing, China, in 1996 and 1998, respectively, and the Ph.D. degree in electrical engineering from Princeton University, Princeton, NJ in 2002.
Speech Title: Recent Advances in Dynamic Processes over Networks
Chong-Yung Chi, National Tsing Hua University, Taiwan
Chong-Yung Chi received Ph.D. degree from the University of Southern California, Los Angeles, California, in 1983 all in Electrical Engineering. Currently, he is Professor of National Tsing Hua University, Hsinchu, Taiwan. He has published more than 240 technical papers, including more than 85 journal papers (mostly in IEEE Trans. Signal Processing), more than 140 peer-reviewed conference papers, 3 book chapters, and 2 books, including a recent textbook, Convex Optimization for Signal Processing and Communications from Fundamentals to Applications, CRC Press, 2017 (which has been popularly used in a series of invited intensive short courses at the top-ranking universities in Mainland China since 2010 before its publication). He received 2018 IEEE Signal Processing Society Best Paper Award, entitled “Outage Constrained Robust Transmit Optimization for Multiuser MISO Downlinks: Tractable Approximations by Conic Optimization,” IEEE Tran. Signal Processing, vol. 62, no. 21, Nov. 2014. His current research interests include signal processing for wireless communications, convex analysis and optimization for blind source separation, biomedical and hyperspectral image analysis, and graph signal processing.
Secrecy Energy Efficiency in Cognitive Radio Networks with Untrusted Secondary Users
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