The lab works across a range of topics — hydroclimatic prediction, agricultural monitoring, climate risk, and the decisions that rest on them. If you like large environmental datasets, forecasting problems, and questions where the answer changes what someone does, there is likely something here for you.
Compound climate extremes represented as hazard footprints, combined with socio-economic vulnerability and linked to observed disaster losses.
Agricultural data production through HarvestStat, and crop yield prediction from satellite data, climate reanalysis and forecasts, and geospatial foundation models.
Open to U of M undergraduates. Python and a willingness to learn are the only prerequisites. Typical work is data harmonization, quality control, and visualization alongside a graduate student. We support applications to the UM Undergraduate Research Award (URA) and the NSERC USRA — get in touch well before the application window opens.
We host visiting students and researchers who bring their own funding. Send a short description of what you would like to work on, the period you have in mind, and your funding source.