EECS Spring 2013 Distinguished Lecture

Vipin Kumar
Research funded by the NSF Expeditions in Computing Program, NASA, and Planetary Skin Institute
University of Minnesota
White Bldg., Room 411
11:30am - 12:30pm
February 28, 2013

Climate change is the defining environmental challenge facing our planet, yet there is considerable uncertainty regarding the social and environmental impact due to the limited capabilities of existing physics-based models of the Earth system. Consequently, important questions relating to food security, water resources, biodiversity, and other socio-economic issues over relevant temporal and spatial scales remain unresolved. A new and transformative approach is required to understand the potential impact of climate change. Data driven approaches that have been highly successful in other scientific disciplines hold significant
potential for application in environmental sciences.

This talk  will present an overview of research being done in a large interdisciplinary project on the development of novel data driven approaches that take advantage of the wealth of climate and ecosystem data now available from satellite and ground-based sensors, the observational record for atmospheric, oceanic, and terrestrial processes, and physics-based climate model simulations. These information-rich datasets offer huge potential for monitoring, understanding, and predicting the behavior of the Earth's ecosystem and for advancing the science of climate change.

This talk will discuss some of the challenges in analyzing such data sets
and our early research results.


Vipin Kumar is currently  William Norris Professor and Head of Computer Science and Engineering  at the University of Minnesota.  His research interests include High Performance computing and data mining, and he is currently leading an NSF Expedition project on understanding climate change using data driven approaches.  He has authored over 250 research articles, and co-edited or coauthored 10 books including the widely used text book ``Introduction to Parallel Computing", and "Introduction to Data Mining" both published by Addison-Wesley.
Kumar 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).
Kumar is a Fellow of the AAAS, ACM and  IEEE. He received the 2009 Distinguished Alumnus Award from the Computer Science Department, University of Maryland College Park,
and 2005 IEEE Computer Society's Technical Achievement Award for his contributions to the design and analysis of parallel algorithms, graph-partitioning, and data mining.
Kumar's 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).