Food for Thought

  • The Commons Hotel- Main Ballroom 615 South Washington Avenue Minneapolis, MN, 55415 United States

Research funded by the NSF Expeditions in Computing Program and  NASA

Vipin Kumar- Regents Professor and William Norris Chair in Large Scale Computing, Department of Computer Science and Engineering, University of Minnesota

Advances in machine learning in conjunction with massive amount of data from Earth observing satellites and other sources offer huge potential for improving food security.  For example, they can help in determining how to feed a growing population  in the world with shrinking amount of land available for growing food due to competition from energy crops and urbanization, while facing stagnant growth in crop yields which may come under further stress due to changing climate.  As another example, they can help provide detailed crop maps and yield estimates by commodity that can be used to identify misalignment with commodity production and import sources so that analysts can anticipate potential consequences  and threats to the food supply chain.  This talk will discuss various challenges involved in analyzing these massive spatio-temporal data sets and some early results.

Brief Bio
Vipin Kumar is a Regents Professor and holds William Norris Chair in the department of Computer Science and Engineering  at the University of Minnesota.  His research interests include data mining, high-performance computing, and their applications in Climate/Ecosystems and health care.  He is currently leading an NSF Expedition project on understanding climate change using data science approaches.  He has authored over 300 research articles, and co-edited or coauthored 10 books including the widely used text book ``Introduction to Parallel Computing", and "Introduction to Data Mining".  Kumar has served as chair/co-chair for many international conferences and workshops in the area of data mining and parallel computing, including 2015 IEEE International Conference on Big Data, IEEE International Conference on Data Mining (2002), and International Parallel and Distributed Processing Symposium (2001).  Kumar is a Fellow of the ACM, IEEE, AAAS, and SIAM.  Kumar's foundational research in data mining and high performance computing has been 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), and the 2016 IEEE Computer Society Sidney Fernbach Award, one of IEEE Computer Society's highest awards. URL: http://www.cs.umn.edu/~kumar