2017 ShanghaiTech Symposium on Information Science and Technology 

Distinguished Speakers

ShanghaiTech Symposium on Information and Science and Technology

Narendra Ahuja

Research Professor of University of Illinois at Urbana-Champaign

Director of Information Technology Research Academy

IEEE Fellow

ACM Fellow

AAAI Fellow


Speech details

Bernd Girod

Professor of Electrical Engineering,Stanford University.

Robert L. and Audrey S. Hancock Professor of Electrical Engineering, Stanford University

Member of the US National Academy of Engineering

IEEE Fellow


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Yann LeCun

Director of AI Research, Facebook.

Founding Director of the NYU Center for Data Science

Silver Professor of Computer Science, Neural Science, and Electrical and Computer Engineering New York University

Member of the US National Academy of Engineering

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Kaifu Li

Founder of Sinovation Ventures

IEEE Fellow


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Jitendra Malik

Arthur J. Chick Professor of EECS,University of California, Berkeley

Member of the US National Academy of Engineering

Member of the US National Academy of Science

IEEE Fellow

ACM Fellow


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Harry Shum

Executive Vice President of Artificial Intelligence & Research at Microsoft.

Member of the US National Academy of Engineering

IEEE Fellow

ACM Fellow


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Dawn Song

Professor of University of California, Berkeley

MacArthur Fellow

Guggenheim Fellow

Alfred P. Sloan Fellow


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Invited Speakers

ShanghaiTech Symposium on Information and Science and Technology

Xilin Chen

Professor of University of Chinese Academy of Science

IEEE Fellow

Fellow of the CCF


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Yuxin Chen

Assistant Professor of Electrical Engineering of Princeton University


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Kyunghyun Cho

Assistant Professor of New York University


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Shenghua Gao

Assistant Professor of ShanghaiTech University


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Yongdae Kim

Professor of Korea Advanced Institute of Science and Technology


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Cheng-Lin Liu

Director, National Laboratory of Pattern Recognition (NLPR)

Vice President, Institute of Automation of Chinese Academy of Sciences


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Tie-Yan Liu

Principal researcher of Microsoft Research Asia.

IEEE Fellow

Distinguished Member of the ACM


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Shiqian Ma

Assistant Professor of The Chinese University of Hong Kong


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Jianbo Shi

Professor of University of Pennsylvania


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Yuandong Tian

Research Scientist of Facebook Inc.


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Kewei Tu

Assistant Professor of ShanghaiTech University


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Xiaofeng Wang

Professor of Indiana University


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Wenyuan Xu

Professor of Zhejiang University


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Wotao Yin

Professor of University of California, Los Angeles


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Junsong Yuan

Associate Professor Program Director of Nanyang Technological University


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Ming Zhou

Assistant Managing Director of Microsoft Research Asia.

IEEE Fellow

Chair of the Chinese Computer Federation’s Chinese Information Technology Committee

Executive Member of the Chinese Information Processing Society


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Industrial Innovation Forum Speakers

ShanghaiTech Symposium on Information and Science and Technology
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Sheng Fu
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Sheng Fu

CEO of Cheetah Mobile, Inc.


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Weiying Ma
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Weiying Ma

Vice President of Bytedance (Toutiao)

Managing Director of Toutiao AI lab


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Shuicheng Yan

Qihoo 360 VP

360 AI Institule Director

360 Chief Scientist


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ShanghaiTech Symposium on Information and Science and Technology

Speakers and Speeches Information

Kyunghyun Cho

Assistant Professor of New York University

Title:Deep Learning, Where are you going?

Abstract:There are three axes along which advances in machine learning and deep learning happen. They are (1) network architectures, (2) learning algorithms and (3) spatio-temporal abstraction. In this talk, I will describe a set of research topics I've pursued in each of these axes. For network architectures, I will describe how recurrent neural networks, which were largely forgotten during 90s and early 2000s, have evolved over time and have finally become a de facto standard in machine translation. I continue on to discussing various learning paradigms, how they related to each other, and how they are combined in order to build a strong learning system. Along this line, I briefly discuss my latest research on designing a query-efficient imitation learning algorithm for autonomous driving. Lastly, I present my view on what it means to be a higher-level learning system. Under this view each and every end-to-end trainable neural network serves as a module, regardless of how they were trained, and interacts with each other in order to solve a higher-level task. I will describe my latest research on trainable decoding algorithm as a first step toward building such a framework.

Bio:Kyunghyun Cho is an assistant professor of computer science and data science at New York University. He was a postdoctoral fellow at University of Montreal until summer 2015, and received PhD and MSc degrees from Aalto University early 2014. He tries best to find a balance among machine learning, natural language processing and life, but often fails to do so.

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Bernd Girod

Professor
Electrical Engineering,Stanford University

Title: From Pixels to Information - Recent Advances in Visual Search

Abstract: With intelligent processing, cameras have great potential to link the real world and the virtual world. We review advances and opportunities for algorithms and applications that retrieve information from large databases using images as queries. For rate-constrained applications, remarkable improvements have been achieved over the course the MPEG-CDVS (Compact Descriptors for Visual Search) standardization. Beyond CDVS lie applications that query video databases with images, while others continually match video frames against image databases. Exploiting the temporal coherence of video for either case can yield large additional gains. We will look at implementations for example applications ranging from text recognition to augmented reality to understand the challenges of building databases for rapid search and scalability, as well as the tradeoffs between processing on a mobile device and in the cloud.

Bio: Bernd Girod is the Robert L. and Audrey S. Hancock Professor of Electrical Engineering at Stanford University, California. He received the Engineering Doctorate degree from University of Hannover, Germany, and the M.S. degree from the Georgia Institute of Technology. Until 1999, he was a Professor with the Electrical Engineering Department, University of Erlangen– Nuremberg. He has authored over 600 conference and journal papers and six books, receiving the EURASIP Signal Processing Best Paper Award in 2002, the IEEE Multimedia Communication Best Paper Award in 2007, the EURASIP Image Communication Best Paper Award in 2008, the EURASIP Signal Processing Most Cited Paper Award in 2008, the EURASIP Technical Achievement Award in 2004, and the Technical Achievement Award of the IEEE Signal Processing Society in 2011. His research interests are in the area of image, video, and multimedia systems. As an entrepreneur, he was involved in numerous startup ventures, among them Polycom, Vivo Software, 8x8, and RealNetworks. He is a Fellow of the IEEE, a EURASIP Fellow, a member of the the National Academy of Engineering, and a member of the German National Academy of Sciences (Leopoldina).

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Shiqian Ma

Assistant Professor
The Chinese University of Hong Kong

Title: Geometric descent method for convex composite minimization

Abstract: We extend the geometric descent method recently proposed by Bubeck, Lee and Singh to tackle nonsmooth and strongly convex composite problems. We prove that our proposed algorithm, dubbed geometric proximal gradient method (GeoPG), converges with a linear rate $(1-1/\sqrt{\kappa})$, and thus achieves the optimal rate among first-order methods, where $\kappa$ is the condition number of the problem. Numerical results on linear regression and logistic regression with elastic net regularization show that GeoPG compares favorably with Nesterov's accelerated proximal gradient method, especially when the problem is ill-conditioned.

Bio: Shiqian Ma received his B.S. from Peking University in 2003, M.S. from Chinese Academy of Sciences in 2006 and Ph.D. in Industrial Engineering and Operations Research from Columbia University in 2011. He then spent one and half years in the Institute for Mathematics and Its Applications at University of Minnesota as an NSF postdoctoral fellow. Shiqian Ma joined the Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong in December 2012. His current research interests include theory and algorithms for large-scale optimization and its applications in big data analytics, statistics, machine learning, bioinformatics, signal processing and image processing. Shiqian Ma received the INFORMS Optimization Society best student paper prize in 2010, honorable mention of INFORMS George Nicholson student paper competition in 2011. He was one of the finalists of the 2011 IBM Herman Goldstine fellowship. He received the Journal of the Operations Research Society of China Excellent Paper Award in 2016.

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Ming Zhou

Assistant Managing Director
Microsoft Research Asia

Title:The new progress of neural machine translation, chatbot and reading comprehension

Abstract:NLP, as one of the most important technology for AI, has made unprecedented progress in recent three years with the rapid and wide use of deep learning approaches. In this presentation, I would like to present the new progress of NLP illustrated by three typical NLP tasks including machine translation (MT), chatbot and reading comprehension. I will share my observations on the challenges of current approaches and discuss the future directions.

Bio:Dr. Ming Zhou is assistant managing director of MSRA in charge of research areas of natural language processing, knowledge mining and enterprise AI, as well as social computing. He is the chair of the Chinese Computer Federation’s (CCF) Chinese Information Technology Committee and an executive member of the Chinese Information Processing Society (CIPS). He is also president-elect of Association of Computational Linguistic (ACL), the most prestigious NLP research association in the world. He developed the first Chinese-English machine translation system in 1989 at Harbin Institute of Technology, and the most famous Chinese-Japanese machine translation product in 1998 at Kodensha Ltd of Japan. He has published over 120 papers at top conferences and journals including 50+ papers at ACL. He obtained his PhD from Harbin Institute of Technology in 1991, and then worked at Tsinghua University as post-doc and associate professor until 1999. He joined Microsoft in 1999 as researcher and became the research manager of its Natural Language Computing Group in 2000.

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