From: Ramasamy Uthurusamy   
   Date: 16 July 2012   
   Subject: ACM SIGKDD 2012 Innovation Award to Prof. Vipin Kumar   
      
   ACM SIGKDD is pleased to announce that Prof. Vipin Kumar   
   is the winner of its 2012 Innovation Award.   
      
   ACM SIGKDD Innovation Award is the highest award for technical   
   excellence in the field of Knowledge Discovery and Data Mining   
   (KDD). It is conferred on one individual or one group of   
   collaborators whose outstanding technical innovations in the KDD   
   field have had a lasting impact in advancing the theory and practice   
   of the field.   
      
   Prof. Vipin Kumar is recognized for his technical contributions to foundational   
   research in data mining as well as its applications to mining scientific   
   data.  Prof.   
   Kumar has made numerous significant and impactful contributions to a wide   
   range of core data mining areas including graph partitioning, clustering,   
   association analysis, high performance and parallel data mining, anomaly/change   
   detection and data driven discovery methods for analyzing global climate and   
   ecosystem data.  Many of his papers on these topics are amongst the most highly   
   cited papers in data mining.   
      
   His early work on graph partitioning (Metis, ParMetis, and related algorithms)   
   with George Karypis is heavily used in social network analysis and serves as   
   the   
   core of Chameleon (one of the most cited clustering algorithms) and CLUTO (one   
   of the most widely used software for clustering).   
      
   His research on the extension of the association analysis paradigm (with Hui   
   Xiong, Pang Tan, Michael Steinbach, Gaurav Pandey, Gang Fang) introduced   
   frameworks  for determining  interestingness of association patterns as well as   
   novel pattern mining concepts and their extensions to handle non-binary data   
   sets.   
   Many of these extensions have enabled novel applications of the association   
   analysis framework to complex biomedical data that are unsuitable for   
   traditional   
   association analysis techniques originally designed for market basket data.   
      
   Prof. Kumar is also well-known for his pioneering research in the areas of high   
   performance and parallel data mining.  In particular, his group was amongst the   
   first ones to introduce the concepts of dynamic load balancing (derived from   
   his   
   earlier extensive work on the design of scalable parallel algorithms for   
   unstructured problems) to the parallel formulations of algorithms such as   
   Apriori and decision tree induction.   
      
   Prof. Kumar's research group has also 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.   
      
   As another example of his leadership in this general area, Prof. Kumar is   
   currently   
   leading a multidisciplinary, multi-institution project on 'Understanding   
   Climate   
   Change' using data driven discovery methods.  This 5-year, $10 Million project   
   is   
   funded by NSF's 'Expeditions in Computing' program that is aimed at pushing   
   the boundaries of computer science research.   
      
   Prof. Kumar co-founded the SIAM International Conferences on Data Mining in   
   2001.  He served as founding co-editor-in-chief of the Journal on Statistical   
   Analysis and Data Mining, which is now the official journal of the American   
   Statistical Association (ASA).  He is the editor of the Chapman & Hall/CRC -   
   Data Mining and Knowledge Discovery book series.  He has authored over 200   
   research articles, and has co-edited or co-authored 11 books including the   
   widely   
   used text books 'Introduction to Parallel Computing' and 'Introduction to Data   
   Mining'.  He has graduated 20+ PhDs, many of whom are leading researchers in   
   academia and at major industrial labs.   
      
   Prof. Kumar received the B.E. in Electronics & Communication Engineering from   
   the Indian Institute of Technology, Roorkee , India , the M.E. in Electronics   
   Engineering from Philips International Institute,  Eindhoven , Netherlands ,   
   and the   
   Ph.D. in Computer Science from the University of Maryland at College Park .   
      
   He is currently William Norris Professor and Head of Computer Science and   
   Engineering Department at the University of Minnesota . Prof. Kumar is a Fellow   
   of ACM, IEEE, and AAAS, and a recipient of the 2009 Distinguished Alumnus   
   Award from the Computer Science Department, University of Maryland College   
   Park, the ICDM 2008 Outstanding Service Award, and the 2005 IEEE Computer   
   Society's Technical Achievement Award.   
      
   The previous SIGKDD Innovation Award winners were Rakesh   
   Agrawal, Jerome Friedman, Heikki Mannila, Jiawei Han, Leo   
   Breiman, Ramakrishnan Srikant, Usama M. Fayyad, Raghu   
   Ramakrishnan, Padhraic Smyth, Christos Faloutsos, and J. Ross Quinlan.   
      
   The award includes a plaque and a check for $2,500 and will be   
   presented at the Opening Plenary Session of the 18th ACM SIGKDD   
   International Conference on Knowledge Discovery and Data Mining,   
   on August 12, 2012 in Beijing , China .   
      
   Prof. Kumar will present the Innovation Award Lecture immediately after   
   the awards presentations.   
      
   ACM SIGKDD is pleased to present Prof. Vipin Kumar its 2012   
   Innovation Award for his foundational technical contributions to the   
   KDD field.   
      
   2012 ACM SIGKDD Awards Committee   
   *        Ramasamy Uthurusamy, Chair   
   *        Chid Apte, IBM Research   
      
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