The 11th ACM International Conference on Web Search and Data Mining

Los Angeles, California, USA, 2018.

Keynotes

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Harry Shum

Executive Vice President
Microsoft

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Bio: Harry Shum is executive vice president of Microsoft’s Artificial Intelligence (AI) and Research group. He is responsible for driving the company’s overall AI strategy and forward-looking research and development efforts spanning infrastructure, services, apps and agents. He oversees AI-focused product groups — the Information Platform Group, Bing and Cortana product groups — and the Ambient Computing and Robotics teams. He also leads Microsoft Research, one of the world’s premier computer science research organizations, and its integration with the engineering teams across the company. Previously, Dr. Shum served as the corporate vice president responsible for Bing search product development from 2007 to 2013. Prior to his engineering leadership role at Bing and online services, he oversaw the research activities at Microsoft Research Asia and the lab’s collaborations with universities in the Asia Pacific region, and was responsible for the Internet Services Research Center, an applied research organization dedicated to advanced technology investment in search and advertising at Microsoft. Dr. Shum joined Microsoft Research in 1996 as a researcher based in Redmond, Washington. In 1998 he moved to Beijing as one of the founding members of Microsoft Research China (later renamed Microsoft Research Asia). There he began a nine-year tenure as a researcher, subsequently moving on to become research manager, assistant managing director and managing director of Microsoft Research Asia and a Distinguished Engineer. Dr. Shum is an IEEE Fellow and an ACM Fellow for his contributions to computer vision and computer graphics. He received his Ph.D. in robotics from the School of Computer Science at Carnegie Mellon University. In 2017, he was elected to the National Academy of Engineering of the United States.

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Andrei Broder

Distinguished Scientist
Google

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Bio: Andrei Broder is a Distinguished Scientist at Google where he leads a multidisciplinary research team located across three continents. From 2005 to 2012 he was a Fellow and VP for Computational Advertising at Yahoo. Previous positions include Distinguished Engineer at IBM and VP for Research and Chief Scientist at AltaVista. He was graduated Summa cum Laude from Technion and obtained his M.Sc. and Ph.D. in Computer Science at Stanford under Don Knuth. Broder has authored more than a hundred papers and was awarded fifty US patents. His current research interests are focused on user understanding, computational advertising, context-driven information supply, and randomized algorithms. He is a member of the US National Academy of Engineering and a Fellow of ACM and of IEEE. Other honors include the ACM Paris Kanellakis Theory and Practice Award and a doctorate Honoris Causa from Technion.

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Shang-Hua Teng

University Professor
USC

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Bio: Shang-Hua Teng is the University Professor and Seeley G. Mudd Professor of Computer Science and Mathematics at University of Southern California. He has twice won the prestigious Gödel Prize in theoretical computer science, first in 2008, for developing the theory of smoothed analysis , and then in 2015, for designing the groundbreaking nearly-linear time Laplacian solver for network systems. Prior to joining USC in 2009, he was a professor at Boston University. He has also taught at MIT, the University of Minnesota, and the University of Illinois at Urbana-Champaign. He has worked at Xerox PARC, NASA Ames Research Center, Intel Corporation, IBM Almaden Research Center, Akamai Technologies, Microsoft Research Redmond, Microsoft Research New England and Microsoft Research Asia. Teng is a Fellow of the Association for Computing Machinery (ACM), as well as an Alfred P. Sloan fellow.

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Igor Perisic

Chief Data Officer
LinkedIn

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Bio: Igor Perisic, Ph.D. is the Chief Data Officer (CDO) and Vice President (VP) of Engineering at LinkedIn. As CDO, he is responsible for all data policy issues and collaborates with our product, security, and legal teams to ensure that we are investing in technology, policies, and controls that will allow LinkedIn to continue to rapidly and safely scale our portfolio of product offerings to an ever broadening audience of members and customers. In addition, Igor Perisic runs LinkedIn’s Data engineering team which focuses on building data infrastructure, personalizing our members experiences through AI and creating Analytics insights and metrics related to our business and members experiences. Igor graduated with a Diplome d’Ingenieur en Mathematique from the Ecole Polytechnique Federale de Lausanne in Switzerland and holds a Ph.D. in Statistics from Harvard.

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Jiawei Han

Abel Bliss Professor
UIUC

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Bio: Jiawei Han is the Abel Bliss Professor in the Department of Computer Science, University of Illinois at Urbana-Champaign. He has been researching into data mining, information network analysis, database systems, and data warehousing. He is a Fellow of ACM and Fellow of IEEE, and received 2004 ACM SIGKDD Innovations Award, 2005 IEEE Computer Society Technical Achievement Award, 2009 IEEE Computer Society Wallace McDowell Award, and 2011 Daniel C. Drucker Eminent Faculty Award at UIUC. His book "Data Mining: Concepts and Techniques" has been adopted as a textbook popularly worldwide.

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Judea Pearl

Turing Award Winner
UCLA

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Bio: Judea Pearl created the representational and computational foundation for the processing of information under uncertainty. He is credited with the invention of Bayesian networks, a mathematical formalism for defining complex probability models, as well as the principal algorithms used for inference in these models. This work not only revolutionized the field of artificial intelligence but also became an important tool for many other branches of engineering and the natural sciences. He later created a mathematical framework for causal inference that has had significant impact in the social sciences. Judea is the 2011 winner of the ACM Turing Award, the highest distinction in computer science, "for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning".

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