ICAI'07: Keynote Lecture

Simultaneous Clustering and Modeling for Large Scale Data Mining Applications Prof. Joydeep Ghosh Schlumberger Distinguished Centennial Chair Professor The University of Texas at Austin, Austin, Texas, USA Date: TBA Time: TBA Location: TBA

Several challenging data mining applications require scalable clustering methods that can also adapt to a wide range of data characteristics. In addition, for such tasks, one is often able to obtain better and more interpretable results by learning separate models on different data segments/clusters, instead of a single complex model. In this talk, I'll first present a simple but versatile clustering framework and then extend it to cater to multi-modal data. The challenge of simulataneous segmentation and learning will then be addressed via a broad conceptual framework. Results will be presented on micro-array data analysis and customer-product data, among others, to highlight the generality and effectiveness of the concepts presented.

Biography

Joydeep Ghosh is currently the Schlumberger Centennial Chair Professor of Electrical and Computer Engineering at the University of Texas, Austin. He joined the UT-Austin faculty in 1988 after being educated at IIT Kanpur, (B. Tech '83) and The University of Southern California (Ph.D’88). He is the founder-director of IDEAL (Intelligent Data Exploration and Analysis Lab) and a Fellow of the IEEE. His research interests lie primarily in intelligent data analysis, data mining and web mining, adaptive multi-learner systems, and their applications to a wide variety of complex engineering and AI problems.

Dr. Ghosh has published more than 200 refereed papers and 30 book chapters, and co-edited 18 books. His research has been supported by the NSF, Yahoo!, Google, ONR, ARO, AFOSR, Intel, IBM, Motorola, TRW, Schlumberger and Dell, among others. He received the 2005 Best Research Paper Award from UT Co-op Society and the 1992 Darlington Award given by the IEEE Circuits and Systems Society for the Best Paper in the areas of CAS/CAD, besides nine other "best paper" awards over the years. He was the Conference Co-Chair of Computational Intelligence and Data Mining (CIDM’07), Program Co-Chair for The SIAM Int'l Conf. on Data Mining (SDM'06), and Conf. Co-Chair for Artificial Neural Networks in Engineering (ANNIE)'93 to '96 and '99 to '03. He is the founding chair of the Data Mining Tech. Committee of the IEEE CI Society. He also serves on the program committee of several top conferences on data mining, neural networks, pattern recognition, and web analytics every year. Dr. Ghosh has been a plenary/keynote speaker on several occasions such as ANNIE’06, MCS 2002 and ANNIE'97 and, and has widely lectured on intelligent analysis of large-scale data. He has co-organized workshops on high dimensional clustering (ICDM 2003; SDM 2005), Web Analytics (with SIAM Int'l Conf. on Data Mining, SDM2002), Web Mining (with SDM 2001), and on Parallel and Distributed Knowledge Discovery ( with KDD-2000).

Dr. Ghosh has served as a consultant or advisor to a variety of companies, from successful startups such as Neonyoyo and Knowledge Discovery One, to large corporations such as IBM, Motorola and Vinson & Elkins. At UT, Dr. Ghosh teaches graduate courses on data mining, artificial neural networks, and web analytics. He was voted the Best Professor by the Software Engineering Executive Education Class of 2004.