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Bio/Description

A Regents Professor at the University of Minnesota, he holds the William Norris Endowed Chair in the Department of Computer Science and Engineering. In May 2015, he was named Regent Professor by the University Of Minnesota Board Of Regents. The designation is the highest level of recognition given to faculty by the University. He received his B.E. degree in Electronics & Communication Engineering from the Indian Institute of Technology Roorkee (formerly, University of Roorkee), India, in 1977; his M.E. degree in Electronics Engineering from Philips International Institute, Eindhoven, Netherlands, in 1979; and his Ph.D. degree in Computer Science from the University of Maryland, College Park in 1982. His current research interests include data mining, high-performance computing, and their applications in Climate/Ecosystems and Biomedical domains. He also served as the Head of the Computer Science and Engineering Department from 2005 to 2015 and as the Director of Army High Performance Computing Research Center (AHPCRC) from 1998 to 2005. His research has resulted in the development of the concept of isoefficiency metric for evaluating the scalability of parallel algorithms, as well as highly efficient parallel algorithms and software for sparse matrix factorization (PSPASES) and graph partitioning (METIS, ParMetis, hMetis). He is the Lead PI of a 5-year, $10 Million project, "Understanding Climate Change - A Data Driven Approach", funded by the National Science Foundation’s (NSF) Expeditions in Computing program that is aimed at pushing the boundaries of computer science research. His research group has been at the forefront in the development of data-driven discovery methods for analyzing global climate and ecosystem data. For example, his research group has developed a series of techniques (starting with a paper in KDD 2003) to automatically identify tele-connections between ocean climate variables (such as sea surface temperature and sea level pressure) and land surface variables (such as temperature and precipitation). Since these tele-connections typically involve phenomena that are separated in space and time, their discovery poses some of the greatest challenges for the KDD community. His team's work on change detection in spatio-temporal data (starting with a paper in KDD 2008) has dramatically advanced current state of the art in the monitoring of global forest cover using satellite data. By applying these methods at the global scale, his team has been able to create comprehensive histories of large-scale changes in the ecosystem due to fires, logging, droughts, flood, farming, etc., that are critical for understanding the relationships of such ecosystem disturbances to global climate variability and human activity. A prototype of this global ecosystem monitoring technology, developed in collaboration with Planetary Skin Institute (PSI), was demonstrated at the COP16, the 16th Climate Change Summit held in Cancun. The release of this prototype was featured in a story in the December 18, 2012 issue of The Economist that specifically cited the data mining capabilities developed at the University of Minnesota as a key enabler for low cost monitoring of the global forest cover that is critically needed in the context of the agreements to save the world's forests. He has authored over 300 research articles, and has co-edited or co-authored 11 books including widely used text books, ``Introduction to Parallel Computing'' and ``Introduction to Data Mining''; both published by Addison Wesley. He is routinely asked to serve on review panels by federal agencies such as DOE, DHS, DOD, and NSF. He has served as Chair/co-Chair for many international conferences and workshops in the area of data mining and parallel computing, including the 2015 IEEE International Conference on Big Data, the IEEE International Conference on Data Mining (2002), and the International Parallel and Distributed Processing Symposium (2001). He co-founded SIAM International Conference on Data Mining and served as a founding co-Editor-In-Chief of Journal of Statistical Analysis and Data Mining (an official journal of the American Statistical Association). Currently, he serves on the steering committees of the SIAM International Conference on Data Mining and the IEEE International Conference on Data Mining, and is series Editor for the Data Mining and Knowledge Discovery Book Series published by CRC Press/Chapman Hall. He is a Fellow of the ACM, IEEE and AAAS. He received the Distinguished Alumnus Award from the Indian Institute of Technology (IIT) Roorkee (2013); the Distinguished Alumnus Award from the Computer Science Department, University of Maryland, College Park (2009), and IEEE Computer Society's Technical Achievement Award (2005) "For contributions to the design and analysis of parallel algorithms, graph partitioning, and data mining". His foundational research in data mining and its applications to scientific data was honored by the ACM SIGKDD 2012 Innovation Award, which is the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD).
  • Noted For:

    Developer of the concept of isoefficiency metric for evaluating the scalability of parallel algorithms; highly efficient parallel algorithms and software for sparse matrix factorization and graph partitioning
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