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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
- Christos Faloutsos, Carnegie Mellon University
- Bing Liu, University of Illinois at Chicago
- Gregory Piatetsky-Shapiro, KDnuggets
- Daryl Pregibon, Google
- J. Ross Quinlan, Rulequest
- Ted Senator, SAIC
- Padhraic Smyth, University of California at Irvine
- Qiang Yang, Hong Kong University of Science and Technology
- Osmar R. Zaiane, University of Alberta, Past Chair
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. The contributions must have significantly influenced the direction of research and development of the field or transferred to practice in significant and innovative ways and/or enabled the development of commercial systems. The award includes a plaque and a check for $2,500 and will be presented at the Opening Ceremony of the annual ACM SIGKDD International Conference on KDD. The Innovation Award recipient presents the Innovation Award Lecture immediately after the awards presentations.
About ACM SIGKDD Service Award
ACM SIGKDD Service Award is the highest service award in the field
of knowledge discovery and data mining (KDD). It is conferred on
one individual or one group for their outstanding professional
services and contributions to the KDD field. Services recognized
include significant contributions to the activities of professional KDD
societies and conferences, leading organizations or projects that
contribute technically to the field as a whole, furthering education
of students, researchers and practitioners of KDD, funding R&D
activities of the KDD community, professional volunteer services in
disseminating technical information to the field, and contributions
to society at large through applications of KDD concepts to improve
global medical care, education, disaster/crisis management,
environment, etc. The award includes a plaque and a check for
$2,500 and will be presented at the Opening Plenary Session of the
annual ACM SIGKDD International Conference on KDD.
About ACM SIGKDD
ACM SIGKDD, ACM's Special Interest Group on Knowledge
Discovery and Data Mining (KDD), is the premier global
professional organization for researchers and professionals
dedicated to the advancement of the science and practice of
knowledge discovery and data mining. It established the Innovation
and Service Awards to recognize outstanding technical and service
contributions to the KDD field.
About ACM
The Association for Computing Machinery (ACM) is the world's
largest educational and scientific computing society, uniting
computing educators, researchers and professionals to inspire
dialogue, share resources and address the field's challenges. ACM
strengthens the computing profession's collective voice through
strong leadership, promotion of the highest standards, and
recognition of technical excellence. ACM supports the professional
growth of its members by providing opportunities for life-long
learning, career development, and professional networking.