Danielle Rasooly, PhD is a biostatistician for the CDC’s Office of Genomics and Precision Public Health. Dr. Rasooly’s specialty is in applying methods in machine learning and causal inference to large-scale medical and genetic data to understand genetic determinants of disease and to inform clinical decision-making. Her current area of interest lies at the intersection of data science, genetics, epidemiology, and public health, involving high-throughput analysis and modeling to understand the underlying biological, genetic, and environmental mechanisms that lead to cardiometabolic diseases. Dr. Rasooly received her Bachelor of Science degree in Mathematics from Stanford University and her Ph.D. in Bioinformatics and Integrative Genomics from Harvard University, where she also completed her post-doctoral training in machine learning, artificial intelligence, and biomedical data science.