Machine Learning Techniques to Monitor Global Agricultural and Environment Change


The University of Minnesota has been awarded a $1.43 million grant from the National Science Foundation to develop machine-learning techniques that can be used to better monitor global agricultural and climate change. A team of researchers from the College of Science and Engineering, the College of Food, Agricultural, and Natural Resources Sciences, and the Minnesota Supercomputing Institute will be working on this project. The Principal Investigator on the grant is MSI PI Vipin Kumar (Computer Science and Engineering); Dr. Jim Wilgenbusch, Senior Associate Director of MSI, is a co-PI. MSI staff will work on the project.

An article about this grant appears on the University’s News site: University of Minnesota to Develop Machine Learning Techniques for Monitoring Global Change.