活动预告 || 2017年数据科学国际研讨会报名正式启动
MIIS 2017 will take place in Shenzhen, at the Chinese University of Hong Kong, Shenzhen, from December 14 to December 17, 2017. The goal of the workshop is to bring together leading scientists, researchers, and practitioners from the world to exchange and share ideas in using mathematics especially modern computation techniques to model and solve practical problems in information science and big data analytics.
2017年数据科学国际研讨会将于香港中文大学（深圳）举行，时间为2017年12月14日至17日。此次研讨会由深圳市大数据研究院与香港中文大学（深圳）联合举办，旨在召集来自世界各地的优秀科学家与研究人员，促进多方合作与交流，共同探讨如何利用现代计算技术来建模并解决在信息科学与大数据分析中所遇到的问题。报名流程如下所示，更多课程详情请点击阅读原文。
1. Scan the following QR code and fill in the registration form.
2. Transfer the registration fee to the following bank account.
3. Send the registration form and a scanned copy of the transfer certificate to the email: stacyluo@sribd.cn.
报名流程
请扫描以下二维码下载报名表
缴纳报名费至指定账户
发送报名表与转账证明至邮箱stacyluo@sribd.cn
报名截止日期
2017年12月13日
Stephen P. Boyd
Stanford University
Stephen P. Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University. He has courtesy appointments in the Department of Management Science and Engineering and the Department of Computer Science, and is member of the Institute for Computational and Mathematical Engineering. His current research focus is on convex optimization applications in control, signal processing, machine learning, and finance.
Professor Boyd received an AB degree in Mathematics, summa cum laude, from Harvard University in 1980, and a PhD in EECS from U. C. Berkeley in 1985. In 1985 he joined the faculty of Stanford's Electrical Engineering Department. He has held visiting Professor positions at Katholieke University (Leuven), McGill University (Montreal), Ecole Polytechnique Federale (Lausanne), Tsinghua University (Beijing), Universite Paul Sabatier (Toulouse), Royal Institute of Technology (Stockholm), Kyoto University, Harbin Institute of Technology, NYU, MIT, UC Berkeley, CUHK-Shenzhen, and IMT Lucca. He holds honorary doctorates from Royal Institute of Technology (KTH), Stockholm, and Catholic University of Louvain (UCL).
Professor Boyd is the author of many research articles and three books: Convex Optimization (with Lieven Vandenberghe, 2004), Linear Matrix Inequalities in System and Control Theory (with L. El Ghaoui, E. Feron, and V. Balakrishnan, 1994), and Linear Controller Design: Limits of Performance (with Craig Barratt, 1991). His group has produced many open source tools, including CVX (with Michael Grant), CVXPY (with Steven Diamond) and Convex.jl (with Madeleine Udell and others), widely used parser-solvers for convex optimization.
Jim Dai
Cornell University
Jim Dai joined Cornell University in 2012 as a professor in the School of Operations Research and Information Engineering (ORIE). Prior joining Cornell, he held the Chandler Family Chair of Industrial and Systems Engineering at Georgia Institute of Technology, where he was a faculty member from 1990 to 2012. He is a Special Term Professor at Tsinghua University. He was a James Riady Distinguished Visiting Professor in Decision Sciences at National University of Singapore (May 2009-Apr 2011), a visiting professor at Aarhus University (Oct 1998-Dec 1998) and Stanford University (Dec 1998-June 1999), and a visiting assistant professor at University of Wisconsin-Madison (Aug 1991-Dec 1991). Dai is an elected fellow of Institute of Mathematical Statistics and an elected fellow of Institute for Operations Research and the Management Sciences (INFORMS).
Mykel Kochenderfer
Stanford University
Mykel Kochenderfer is Assistant Professor of Aeronautics and Astronautics and Assistant Professor, by courtesy, of Computer Science at Stanford University. He received his Ph.D. from the University of Edinburgh in 2006 where he studied at the Institute of Perception, Action and Behaviour in the School of Informatics. He received B.S. and M.S. degrees in computer science from Stanford University in 2003. Prof. Kochenderfer is the director of the Stanford Intelligent Systems Laboratory (SISL), conducting research on advanced algorithms and analytical methods for the design of robust decision making systems. Of particular interest are systems for air traffic control, unmanned aircraft, and other aerospace applications where decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency. Research at SISL focuses on efficient computational methods for deriving optimal decision strategies from high-dimensional, probabilistic problem representations.
Bill Lin
University of California, San Diego
Bill Lin currently works on all aspects of network and VLSI architecture problems, including the design of data networks, high-performance switches and routers, high-speed network measurement mechanisms, and on-chip interconnection networks. He is also interested in the design of multiprocessor Systems-on-Chips and 3D chip architectures. He holds a BS, a MS, and a Ph.D. degree in Electrical Engineering and Computer Sciences from the University of California, Berkeley. He is currently a Professor in the Department of Electrical and Computer Engineering at UCSD where he has been actively involved with the Center for Wireless Communications (CWC), the Center for Networked Systems (CNS), and the California Institute for Telecommunicatons and Information Technology (Calit2). He is also currently an Adjunct Professor in the Department of Computer Science and Engineering at UCSD. Prior to joining UCSD, he was the head of the System Control and Communications Group at IMEC where he led a research team that worked on various aspects of VLSI architectures, system design methodologies, and systems-on-chip applications. He has co-authored over 160 journal and conference publications, including 2 Best Paper awards, 3 Best Paper nominations, and 2 Distinguished Paper citations. He has served on panels and given invited presentations at several major conferences, and he has served on over 50 program committees, including serving as the General Chair for NOCS-2009, ANSC-2010, and IWQoS-2011. He also holds 4 awarded patents.
Zhouchen Lin
Peking University
Zhouchen Lin received the Ph.D. degree in applied mathematics from Peking University in 2000. He worked in MSRA between 1999 and 2012, including his internship. He is currently a Professor at Key Laboratory of Machine Perception (MOE), School of Electronics Engineering and Computer Science, Peking University. His research interests include computer vision, image processing, machine learning, pattern recognition, and numerical optimization. He is an area chair of CVPR 20142016, ICCV 2015 and NIPS 2015 and a senior program committee member of AAAI 20162017/2018 and IJCAI 2016. He is an associate editor of IEEE Trans. Pattern Analysis and Machine Intelligence and International J. Computer Vision. He is an IAPR Fellow.
Pinyan Lu
Shanghai University
of Finance and Economics
Pinyan Lu is a professor and the founding director of Institute for Theoretical Computer Science at Shanghai University of Finance and Economics (ITCS@SUFE). Before joining SUFE, he was a researcher at Microsoft Research. He is also a visiting Chair Professor of Shanghai Jiao Tong University. He studied in Tsinghua University (BS (2005) and PhD (2009) both in Computer Science). He is interested in theoretical computer science, including complexity theory, algorithms design and algorithmic game theory. Currently, his research is mainly focused on complexity and approximability of counting problems, and algorithmic mechanism design.
Pinyan is the recipient of a number of awards including CCF Young Scientist award, Best Paper Award from ICALP 2007, FAW 2010, ISAAC 2010 and so on. He was invited to deliver a 45-mins invited talk at the International Congress of Chinese Mathematicians (ICCM 2010). He is the PC chairs for FAW-AAIM 2012, WINE 2017, FAW 2018 and so on, and PC members for STOC 2013, FOCS 2015, and a dozen of international conference. He is an Editorial Board Member of the Journal of Discrete Algorithms
John C.S. Lui
The Chinese University
of Hong Kong
John C.S. Lui is currently the Choh-Ming Li Professor of the CSE Department at The Chinese University of Hong Kong (CUHK) and the associate dean of research at the College of Engineering. His current research interests are in network sciences, network economics, networksystem security (e.g., cloud security, mobile security, …etc), large scale distributed systems and performance evaluation theory. John received various departmental teaching awards and the CUHK Vice-Chancellor's Exemplary Teaching Award, as well as the CUHK Faculty of Engineering Research Excellence Award (2011-2012). He is a co-recipient of the IFIP WG 7.3 Performance 2005, IEEEIFIP NOMS 2006 and SIMPLEX’14 Best Paper Awards. He is an elected member of the IFIP WG 7.3, Fellow of ACM, Fellow of IEEE, Senior Research Fellow of the Croucher Foundation and the past chair of the ACM SIGMETRICS (2011-15). His personal interests include films and general reading.
Tao Mei
Microsoft Research Asia
Tao Mei is a Senior Researcher and Research Manager with Microsoft Research Asia. His current research interests include multimedia analysis and computer vision. He is leading a team working on image and video analysis, vision and language, and multimedia search. He has authored or co-authored over 150 papers with 11 best paper awards. He holds over 50 filed U.S. patents (with 20 granted) and has shipped a dozen inventions and technologies to Microsoft products and services. He is an Editorial Board Member of IEEE Trans. on Multimedia, ACM Trans. on Multimedia Computing, Communications, and Applications, and Pattern Recognition. He is the General Co-chair of IEEE ICME 2019, the Program Co-chair of ACM Multimedia 2018, IEEE ICME 2015, and IEEE MMSP 2015. Tao is as a Fellow of IAPR and a Distinguished Scientist of ACM.
Satinder Singh
University of Michigan
Satinder Singh received the B.Tech degree in electrical engineering from the Indian Institute of Technology, New Delhi, India, in 1987, and the Ph.D. degree in computer science from the University of Massachusetts, Amherst, MA, USA in 1993. He is a Professor of Computer Science and Engineering at the University of Michigan, Ann Arbor, MI, USA. He is Director of the Artificial Intelligence Laboratory at the University of Michigan. His main research interest is in the old-fashioned goal of Artificial Intelligence (AI), that of building autonomous agents that can learn to be broadly competent in complex, dynamic, and uncertain environments.
Ruoyu Sun
University of Illinois
at Urbana-Champaign
Ruoyu Sun is an assistant professor in UIUC IS&E department. Previously he worked at FAIR (Facebook Artificial Intelligence Research) as a (full-time) visiting researcher. Before that he was a postdoctoral scholar in Dept. of Management Science & Engineering at Stanford University, working with Yinyu Ye. He obtained my Ph.D. in Electrical Engineering at the University of Minnesota in 2015, under the supervision of Zhi-Quan (Tom) Luo. He received the B.Sc. degree in mathematics from Peking University, Beijing, China in 2009.
His research interest mainly lies in large-scale optimization and its application in machine learning, data analysis and signal processing. He has also worked on signal processing and information theory for wireless networks. He has received the second place of INFORMS Nicholson student paper competition for his work on randomly permuted ADMM, and the honorable mention of INFORMS optimization society student paper prize on matrix completion via non-convex factorization.
Lieven Vandenberghe
University of California,
Los Angeles
Lieven Vandenberghe is Professor in the Electrical and Computer Engineering Department at the University of California, Los Angeles, with a joint appointment in the Department of Mathematics. He received a Ph.D. in Electrical Engineering from K.U. Leuven, Belgium, in 1992. He joined UCLA in 1997, following postdoctoral appointments at K.U. Leuven and Stanford University, and has held visiting professor positions at K.U. Leuven and the Technical University of Denmark. He is coauthor (with Stephen Boyd) of the book Convex Optimization (2004) and editor (with Henry Wolkowicz and Romesh Saigal) of the Handbook of Semidefinite Programming (2000). His research interests are in optimization, systems and control, and signal processing.
Mengdi Wang
Princeton University
Mengdi Wang is interested in data-driven stochastic optimization and applications in machine and reinforcement learning. She received her PhD in Electrical Engineering and Computer Science from Massachusetts Institute of Technology in 2013. At MIT, Mengdi was affiliated with the Laboratory for Information and Decision Systems and was advised by Dimitri P. Bertsekas. Mengdi became an assistant professor at Princeton in 2014. She received the Young Researcher Prize in Continuous Optimization of the Mathematical Optimization Society in 2016 (awarded once every three years), the Princeton SEAS Innovation Award in 2016, and the NSF Career Award in 2017.
Hongkai Xiong
Shanghai Jiao
Tong University
Hongkai Xiong is currently a Full Professor in the Department of Electronic Engineering, Shanghai Jiao Tong University (SJTU). Since he received Ph. D degree from SJTU in 2003, he has been with the Department of Electronic Engineering, SJTU. From Dec. 2007 to Dec. 2008, Dr. Xiong was a Research Scholar with the Department of Electrical and Computer Engineering, Carnegie Mellon University (CMU), PA, USA. He has ever been a visiting scholar in the Division of Biomedical Informatics (DBMI) at the University of California, San Diego (UCSD)
His research interests include signal processing, multimedia communication, source coding and computer vision. He published over 150 refereed journal and conference papers. His research projects are funded by NSF, QUALCOMM, MICROSOFT, and INTEL. He is the recipient of the Best Student Paper Award for “Spatio-Temporal Coherence for 3-D View Synthesis with Curve-Based Disparity Warping” at the 2014 IEEE Visual Communication and Image Processing (IEEE VCIP’14), the Best Paper Award for “Strip Based Media Retargeting via Combing Multi Operators” at the 2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (IEEE BMSB’13), and the Top 10% Paper Award for “Super-Resolution Reconstruction with Prior Manifold on Primitive Patches for Video Compression” at the 2011 IEEE International Workshop on Multimedia Signal Processing (IEEE MMSP’11). He served as TPC members for prestigious conferences such as ACM Multimedia, ICIP, ICME, and ISCAS.
In 2014, he was granted National Science Fund for Distinguished Young Scholar and Shanghai Youth Science and Technology Talent as well. In 2013, he was awarded a recipient of Shanghai Shu Guang Scholar. From 2012, he is a member of Innovative Research Groups of the National Natural Science. In 2011, he obtained the First Prize of the Shanghai Technological Innovation Award for “Network-oriented Video Processing and Dissemination: Theory and Technology”. In 2010 and 2013, he obtained the SMC-A Excellent Young Faculty Award of Shanghai Jiao Tong University. In 2009, he was awarded a recipient of New Century Excellent Talents in University, Ministry of Education of China. He is a senior member of the IEEE (2010).
Zhengyuan (Daniel) Xu
University of Science
and Technology of China
Zhengyuan (Daniel) Xu received the B.S. and M.S. degrees from Tsinghua University, Beijing, China, in 1989 and 1991, respec- tively, and the Ph.D. degree from Stevens Institute of Technology, NJ, USA, in 1999. From 1991 to 1996, he was with Tsinghua Unisplendour Group Corporation, Tsinghua University, as System Engi- neer and Department Manager. In 1999, he joined University of California, Riverside, first as Assistant Professor and then tenured Associate Professor and Professor. He was Founding Director of the multi- campus Center for Ubiquitous Communication by Light (UC-Light), University of California. In 2010, he was selected by the “Thousand Talents Program” of China, appointed as Professor at Tsinghua University, and then joined University of Science and Technology of China (USTC). He is Founding Director of the Optical Wireless Communication and Network Center of USTC, Founding Director of Wireless-Optical Communications Key Laboratory of Chinese Academy of Sciences, and a Chief Scientist of the National Key Basic Research Program (973 Program) of China. His research focuses on wireless communication and networking, optical wireless communications, geolocation, intelligent transportation, and signal processing. He has published over 200 journal and conference papers. He has served as an Associate Editor and Guest Editor for different IEEE journals, and serves as Associate Editor for the OSA/SIOM journal Photonics Research and Guest Editor for IEEE JSAC—Special Issue on Optical Wireless Communications. He was a Founding Chair of IEEE Workshop on Optical Wireless Communications.
Junshan Zhang
Arizona State University
Junshan Zhang received his Ph.D. degree from the School of ECE at Purdue University in 2000. He joined the School of ECEE at Arizona State University in August 2000, where he has been Fulton Chair Professor since 2015. His research interests fall in the general field of information networks and data science, including communication networks, Internet of Things (IoT), Fog Computing, social networks, smart grid. His current research focuses on fundamental problems in information networks and data science, including Fog Computing and its applications in IoT and 5G, IoT data privacysecurity, optimizationcontrol of mobile social networks, cognitive radio networks, stochastic modeling and control for smart grid.
Prof. Zhang is a Fellow of the IEEE, and a recipient of the ONR Young Investigator Award in 2005 and the NSF CAREER award in 2003. He received the IEEE Wireless Communication Technical Committee Recognition Award in 2016. His papers have won a few awards, including the Kenneth C. Sevcik Outstanding Student Paper Award of ACM SIGMETRICS/IFIP Performance 2016, the Best Paper Runner-up Award of IEEE INFOCOM 2009 and IEEE INFOCOM 2014, and the Best Paper Award at IEEE ICC 2008 and ICC 2017. Building on his research findings, he co-founded Smartiply Inc in 2015, a Fog Computing startup company delivering boosted network connectivity and embedded artificial intelligence.
Prof. Zhang was TPC co-chair for a number of major conferences in communication networks, including IEEE INFOCOM 2012 and ACM MOBIHOC 2015. He was the general chair for ACMIEEE SEC 2017, WiOPT 2016, and IEEE Communication Theory Workshop 2007. He was a Distinguished Lecturer of the IEEE Communications Society. He was an Associate Editor for IEEE Transactions on Wireless Communications, an editor for the Computer Network journal, and an editor IEEE Wireless Communication Magazine. He is currently serving as an editor-at-large for IEEEACM Transactions on Networking and an editor for IEEE Network Magazine.
Tong Zhang
Tencent
Tong Zhang is a machine learning researcher, and the executive director of Tencent AI Lab. Previously, he was a professor at Rutgers university, and worked at IBM, Yahoo, and Baidu. Tong Zhang's research interests include machine learning algorithms and theory, statistical methods for big data and their applications. His research has been supported by many grants from funding agencies such as NSF and NIH. He is a fellow of ASA and IMS, and he has been in the editorial boards of leading machine learning journals and program committees of top machine learning conferences. His Google scholar page can be found here.
Tong Zhang received a B.A. in mathematics and computer science from Cornell University and a Ph.D. in Computer Science from Stanford University.
Weifeng Zhang
Alibaba
Weifeng Zhang is a researcher and senior director at Alibaba Infrastructure Services Group, interested in heterogeneous acceleration for machine learning. Prior to joining Alibaba, he was a director at Qualcomm Inc, San Diego, focusing on compilation and optimization of Qualcomm Adreno graphics processing unit (GPU). He was also a Qualcomm representative at Khronos Group, looking into the next-generation of industrial standards of lightweight computation APIs and neural network exchange format. Weifeng Zhang received a B.S. in electrical engineering from Wuhan University, China, and Ph.D in computer science & engineering from University of California, San Diego.
Date
Program
2017/12/14 afternoon
Tutorial
2017/12/15-16 full day
Invited talks
2017/12/17 morning
Invited talks
2017/12/15 night
Banquet