Christos Faloutsos, Professor at Dept. of Computer Science, Carnegie Mellon University.

What do graphs look like? How do they evolve over time? How to handle a graph with a billion nodes? We present a comprehensive list of static and temporal laws, and some recent observations on real graphs (like, e.g., “eigenSpokes”). For generators, we describe some recent ones, which naturally match all of the known properties of real graphs. Finally, for tools, we present “oddBall” for discovering anomalies and patterns, as well as an overview of the PEGASUS system which is designed for handling Billion-node graphs, running on top of the “hadoop” system.

Christos Faloutsos is a Professor at Carnegie Mellon University. He has received the Presidential Young Investigator Award by the National Science Foundation (1989), the Research Contributions Award in ICDM 2006, the SIGKDD Innovations Award (2010) sixteen “best paper” awards, and four teaching awards. He has served as a member of the executive committee of SIGKDD; he has published over 200 refereed articles, 11 book chapters and one monograph. He holds five patents and he has given over 30 tutorials and over 10 invited distinguished lectures. His research interests include data mining for graphs and streams, fractals, database performance, and indexing for multimedia and bio-informatics data.

Friday, 8:30-9:30 AM

Harry Shum, VP of Search Product Development, Microsoft.

The decade-old Internet search outcomes, manifested in the form of “ten blue links,” are no longer sufficient for Internet users. Many studies have shown that when users are ushered off the conventional search result pages through blue links, their needs are often partially met at best in a “hit-or-miss” fashion. To tackle this challenge, we have designed Bing, Microsoft’s decision engine, to not just navigate users to a landing page through a blue link but to continue engaging with users to clarify intent and facilitate task completion. Underlying this new paradigm is the Bing Dialog Model that consists of three building blocks: an indexing system that comprehensively collects information from the web and systematically harvests knowledge, an intent model that statistically infers user intent and predicts next action, and an interaction model that elicits user intent through mathematically optimized presentations of web information and domain knowledge that matches user needs. In this talk, I’ll describe Bing Dialog Model in details and demonstrate it in action through some innovative features since the launch of www.Bing.com .

Harry Shum is the corporate vice president responsible for search product development at Microsoft Corp. Previously 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 long-term and short-term technology investments in search and advertising at Microsoft.

Shum joined Microsoft Research in 1996, as a researcher based in Redmond, Wash. 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 research manager, subsequently moving on to become assistant managing director, managing director of Microsoft Research Asia, Distinguished Engineer and corporate vice president.

Shum is an Institute of Electrical and Electronics Engineers Fellow and an Association for Computing Machinery Fellow for his contributions on computer vision and computer graphics. He has published more than 100 papers about computer vision, computer graphics, pattern recognition, statistical learning and robotics. He holds more than 50 U.S. patents.

Shum received a doctorate in robotics from the School of Computer Science at Carnegie Mellon University in Pittsburgh. In his spare time he enjoys playing basketball, rooting for the Pittsburgh Steelers and spending time with his family.