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Keynote Speakers


Wednesday, December 8, 2010 9.15-10.30 AM


sbDr. Stephen Brobst

Chief Technology Officer, Teradata Corporation, USA.








Title: The Future of Data Warehousing



This talk examines key trends in data warehouse deployment and developments in advanced technology. Specific areas of focus include: (1) data acquisition and delivery, (2) operational intelligence in the real-time enterprise, and (3) analytic applications architecture. The implications of these technology developments for data warehouse implementations will be discussed with examples from across a number of different industries.



Stephen Brobst is the Chief Technology Officer for Teradata Corporation. His specialization is in the design and construction of data warehouse solutions for Fortune 500 companies in the United States and internationally. Stephen performed his graduate work in Computer Science at the Massachusetts Institute of Technology where his Masters and PhD research focused on high-performance parallel processing. He also completed an MBA with joint course and thesis work at the Harvard Business School and the MIT Sloan School of Management. Stephen has authored numerous books and articles related to advanced data management techniques. Stephen has recently been appointed to Barrack Obama's Presidential Council of Advisors on Science and Technology (PAST) in the working group on Networking and Information Technology Research and Development (NITRD).

Thursday, December 9, 2010 9.00-10.15 AM


daProf. Divyakant Agrawal

University of California, Santa Barbara, USA.



 Title: Scalable Data Management in the Cloud: Research Challenges and Opportunities:



Over the past two decades, database and systems researchers have made significant advances in the development of algorithms and techniques to provide data management solutions that carefully balance the three major requirements when dealing with critical data: high availability, scalability, and data consistency.  However, over the past few years the data requirements, in terms of availability and scalability, from Internet scale enterprises that provide services and cater to millions of users has been unprecedented. Current proposed solutions to scalable data management, driven primarily by prevalent application requirements, significantly downplay the data consistency requirements and instead focus on very high availability and almost unlimited scalability to support data-rich applications for millions to tens of millions of users.  In particular, the "newer" data management systems limit consistent access only at the granularity of single objects, rows, or keys, thereby significantly trading-off consistency in order to achieve very high scalability and availability. But the growing popularity of "cloud computing", the resulting shift of a large number of Internet applications to the cloud, and the quest towards providing data management services in the cloud, has opened up the challenge for designing data management systems that provide consistency guarantees at a granularity which goes beyond single rows and keys. In this talk, we analyze the design choices that allowed modern scalable data management systems to achieve orders of magnitude higher levels of scalability compared to traditional databases. With this understanding, we highlight some design principles for data management systems providing scalable and consistent data management as a service in the cloud.  Slides



Dr. Divyakant Agrawal is a Professor of Computer Science at the University of California at Santa Barbara. His research expertise is in the areas of database systems, distributed computing, data warehousing, and large-scale information systems. He served as VP of Data Solutions and Advertising Systems at the Internet Search Company where hedeveloped revenue-sensitive products at by applying data-mining and machine-learning technologies over’s historical data. He has served extensively on the Program Committees of International Conferences, Symposia, and Workshops and served as an editor of the journal of Distributed and Parallel Databases, the VLDB journal and currently serves on the editorial board of the Proceedings of the VLDB. He recently served as the Program Chair of the 2010 ACM International Conference on Management of Data and is currently serving as the General Chair of the 2010 ACM SIGSPATIAL Conference on Advances in Geographical Information Systems. His research philosophy is to work on data management problems that have both practical as well as theoretical impact. He has published approximately 300 research manuscripts in prestigious forums (journals, conferences, symposia, and workshops) on wide range of topics related to data management and distributed systems. Recently, Dr. Agrawal has been recognized as an ACM Distinguished Scientist.

Friday, December 10, 2010 9.15-10.30 AM


scProf. Soumen Chakrabarti

Department of Computer Science

Indian Institute of Technology, Bombay.




Title: Making Web-scale Entity-Relationship Search a Reality   



Over 99% of queries to Web search engines contain a noun, often referring to an entity.  Entity catalogs like WordNet and Wikipedia list millions of well-known entities.  Bootstrapping techniques may help us expand that to hundreds of millions of people, millions of locations, books, songs, and other artifacts. The next problem in Web search is to represent, index, query and rank in a fine-grained graph-structured setting where dozens to hundreds of tokens on Web pages are annotated with entities, which in turn have attributes as well as type, subclass and other relational linkages. We will discuss recent advances in indexing, proximity models in information retrieval, entity annotation, graph search and mining, and machine learning for ranking that are coming together to take us to the next level of search.


At IIT Bombay, we are building a system to search the annotated Web that scales to 500 million pages and all entities and categories in Wikipedia. The prototype runs on a 40-host multicore cluster. We plan to answer typed entity queries (German physicist teaching at Princeton, typical driving time between Mumbai and Pune) and relation queries (tuples with mathematicians and musical instruments they played). We will present some of the challenges we faced on the way, and initial experience with the system.  Slides



Soumen Chakrabarti received his Ph.D. in Computer Science from the University of California, Berkeley. At Berkeley he worked on compilers and runtime systems for running scalable parallel scientific software on message passing multiprocessors.

He was a Research Staff Member at IBM Almaden Research Center where he worked on the Clever Web search project and led the Focused Crawling project.

In 1999 he joined the Department of Computer Science and Engineering at the Indian Institute of Technology, Bombay. He also severed as Visiting Associate Professor at Carnegie-Mellon University.

His current research interests include integrating, searching, and mining text and graph data models, exploiting types and relations in search, and dynamic personalization in graph-based retrieval and ranking models.