Department of Medicine and the College
Brett Beaulieu-Jones applies machine learning to health care data to extract insights relevant to biology and health care delivery. His research group uses machine learning to precisely define phenotypes from large-scale biomedical data repositories, such as those contained in clinical records, with particular interest in complex neurological conditions, including Parkinson’s disease and epilepsy. His research also seeks to understand the relationship between technology and health care delivery, including the deployment of machine learning and informatics tools, and the extraction of robust insights from real-world biomedical data.
Beaulieu-Jones received a National Institutes of Health Pathway to Independence Award from the National Institute of Neurological Disorders and Stroke. He has had multiple publications recognized among the American Medical Informatics Association’s Year in Review top 10 papers in clinical informatics.
He earned his PhD in genomics and computational biology from the Perelman School of Medicine at the University of Pennsylvania. His thesis, which was recognized by the American Medical Informatics Association, focused on the development and application of machine learning and informatics methods to clinical data to identify biologically or clinically interesting patient subpopulations. He then completed a postdoctoral fellowship and served as a junior faculty member in the Department of Biomedical Informatics at Harvard Medical School.