- Bioinformatics and statistics
- Digital agriculture
- Agronomic forecasting (Dokoohaki Lab)
- Tools for testing hypotheses (Lipka Lab)
- Evolutionary Bioinformatics (GCA Lab)
- Small Grains (Rutkoski Lab)
Agriculture has been a data-rich discipline for decades (modern statistics was developed to make sense of agricultural data sets), and it’s even more so today. Huge amounts of data are being generated by agricultural equipment, communications and sensing devices, markets and experiments. Our researchers are leading the way in taming and explaining agricultural data for the 21st century.