As one of Geneia’s principal data scientists, Jasmine is responsible for building predictive models for adverse health outcomes. She is currently focused on developing algorithms for chronic disease risk identification.
Prior to joining Geneia, Jasmine generated predictive models for identification of Parkinson’s disease in patients as a Fellow with the Insight Health Data Science program. With a background as a genetics researcher at the Whitehead Institute, she also brings extensive knowledge of biomedical science into her work as a healthcare data scientist.
Jasmine completed her PhD in molecular and cell biology from UC Berkeley, and holds a BA in biology from Oberlin College. In her spare time, she enjoys playing board games, running, and experimenting with baking the perfect muffin.