Alex Anderson-Frey is an atmospheric scientist who focuses on mesoscale meteorology and the study of severe storms. Her research interests range from using machine learning techniques to tease out the environmental conditions most conducive to the development of tornado outbreaks, to exploring why some storms result in tornadoes and others don’t, to describing the growing intersection of risk and exposure to deadly storms, to reevaluating one-size-fits-all forecasting techniques in atypical severe weather scenarios, to filling gaps in the severe storm record (especially outside of the United States), to using cloud-scale models to simulate severe weather scenarios, to taking a step back and determining how to define a “good” severe weather warning. She’s also happy to help students, researchers and faculty alike to learn more about the ways in which machine learning can help them ask the right questions. She is dedicated to ensuring that undergraduate students have the programming know-how that will serve them well wherever they go, and her teaching is always with the aim of fostering and encouraging students’ confidence as scientists.