Dr. Juliet Edgcomb is an Assistant Professor at the University of California Los Angeles. She is a child psychiatrist and physician informaticist whose research focuses evolving the use of electronic health records (EHRs) to detect, predict, and inform precision approaches to suicide prevention and progression of mental illness among children. Dr. Edgcomb is the principal investigator of a five-year Mentored Patient-Oriented Career Development Award (K23) from the National Institute of Mental Health (K23MH130745-01) through which she is developing machine learning algorithms to derive trajectories and stratify risk of suicidal behavior using large healthcare datasets. Her research has been supported by the American Foundation for Suicide Prevention, Brain and Behavior Research Foundation, American Psychiatric Association, Thrasher Research Fund, Foundation for the National Institute of Health, and Harvey T. and Maude C. Sorensen Foundation. Her work as a physician-scientist strives to advance the interface of clinical informatics and precision interventions to understand, prevent, and intervene on trajectories of childhood-onset mental illness from a developmentally-informed perspective.