Graduate Student Jamin Rader’s ML Research Featured by the DOE CSGF Program
ATS graduate student Jamin Rader’s Ph.D research that applies machine learning to climate prediction was featured by DOE in the 2023 edition of the Computational Science Graduate Fellowship Program DEIXIS magazine. The article follows the arc from Jamin’s early interest in weather to his recent work using ML to explore predictability in weather and climate. The article highlights the power of interpretable AI for climate research, which Jamin says “comes from the idea that we can make neural networks think a little bit like us.” The piece describes Jamin’s success in applying interpretable ML to understand preconditions for the formation of El Niño. The entire DEIXIS volume can be found here: https://www.krellinst.org/doecsgf/docs/deixis/deixis2023.pdf.