Keynote Speaker


 Usama M. Fayyad
Chairman & CTO of ChoozOn Corporation/Blue Kangaroo  
Bio:

Usama M. Fayyad, Ph.D. is Chairman & CTO of ChoozOn Corporation/Blue Kangaroo. Up until September 2008, he was in Sunnyvale, CA as Yahoo!'s chief data officer & Executive VP responsible for Yahoo!'s global data strategy, policies and systems, investments, and data analytics and infrastructure which processed over 25 Terabytes of data per day. Fayyad also founded and managed the Yahoo! Research Labs and several companies. He is a Fellow of the AAAI (Association for Advancement of Artificial Intelligence) and a Fellow of the ACM (Association of Computing Machinery). He is ACM SIGKDD’s Chairman which runs the world’s premiere data science, big data, and data mining conferences: KDD, and was founding editor-in-chief of SIGKDD Explorations Newsletter.


Topic: The What, Why, How of Big Data: Opportunities in On-line Predictive Analytics

Virtually all organizations are having to deal with Big Data in many contexts: marketing, operations, monitoring, performance, and even financial management. Big Data is characterized not just by its size, but by its Velocity and its Variety for which keeping up with the data flux, let alone its analysis, is challenging at best and impossible in many cases. In this talk I will cover some of the basics in terms of infrastructure and design considerations for effective an efficient BigData. In many organizations, the lack of consideration of effective infrastructure and data management leads to unnecessarily expensive systems that fail the cost/benefits analysis. We will refer to example frameworks and clarify the kinds of operations where Map-Reduce (Hadoop and and its derivatives) are appropriate and the situations where other infrastructure is needed to perform segmentation, prediction, analysis, and reporting appropriately – these being the fundamental operations in predictive analytics. We will then pay specific attention to on-line data and the unique challenges and opportunities represented there. We cover examples of Predictive Analytics over Big Data with case studies in eCommerce Marketing, on-line publishing and recommendation systems, and advertising targeting, and we conclude with some case studies in Social Network data.

 
Brian Pink
Australian Statistician, Australian Bureau of Statistics
Bio

Brian took up his appointment as Australian Statistician on Monday, 5 March 2007. His career in official statistics is a long one, starting in Australia with the then Commonwealth Bureau of Census and Statistics in Sydney in 1966. He was Government Statistician and Chief Executive of Statistics New Zealand from late October 2000 to 2 March 2007. He is Chairman of the OECD Committee on Statistics, Chair of the Statistics Committee of ESCAP and Vice Chair of the United Nations Statistical Commission. Back home he is an ex officio member of the Australian Statistics Advisory Council and an Australian Electoral Commissioner. Brian is passionate about the importance of the role of official statistics in society. Brian has been instrumental in championing a significant information management transformation program to prepare the ABS, the NSS and the international statistical community to meet the growing challenges of providing information, which will be needed by policy makers, government and businesses in the future.

Topic:Big Data and Official Statistics – Some Observations
   

Philip S Yu
Professor and Wexler Chair in Information Technology, University of Illinois at Chicago
Bio:

Philip S. Yu is currently a Professor in the Department of Computer Science at the University of Illinois at Chicago and also holds the Wexler Chair in Information Technology.   He spent most of his career at IBM Thomas J. Watson Research Center and was manager of the Software Tools and Techniques group. His research interests include big data, data mining, privacy preserving data publishing, data stream, social networking, and database systems. Dr. Yu has published more than 730 papers in refereed journals and conferences with an h-index of 100. He holds or has applied for more than 250 US patents. Dr. Yu is a Fellow of the ACM and the IEEE.  He is the Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data.

Topic:On Mining Big Data

The problem of big data has become increasingly importance in recent years. On the one hand, the big data is an asset that potentially can offer tremendous value or reward to the data owner. On the other hand, it poses tremendous challenges to realize the value out of the big data. The very nature of the big data poses challenges not only due to its volume, and velocity of being generated, but also its variety and veracity. Here variety means the data collected from various sources can have different formats from structured data to text to network/graph data to image, etc. Veracity concerns the trustworthiness of the data as the various data sources can have different reliability. In this talk, we will discuss these issues and approaches to address them.