A New IDEA: Pairing Trainees with Computational Experts During the Pandemic
This spring in the midst of a pandemic, a committee of CALS faculty members matched graduate students and postdocs with data they needed to analyze or model computationally to computational experts with the necessary expertise. Learn more about how the collaboration is going for three trainees.
Plant Aid: A GRIP4PSI Big-Data Project to Detect Plant Diseases Faster
An interdisciplinary team led by professor Jean Ristaino will combine small sensors with big data for faster detection of the diseases plaguing tomato fields. From a hand-held plant disease ‘sniffer’ to a cloud-based database that can alert farmers about the cause of the stress and suggest possible mitigation strategies, the project aims to detect diseases early, improving yield.
Fred Gould: My Journey to Interdisciplinary Research
Fred Gould shares his journey from graduate school to interdisciplinary research on genetically modified pests and beyond, as well as the challenges he overcame along the way.