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Andrew Loza is a physician-scientist whose research focuses on predictive analytics in population health. He obtained his PhD from Washington University in St. Louis in biophysics, where he studied mechanisms of collective cell migration using time-lapse microscopy, computer vision, and simulation techniques. He completed his MD degree at Yale University School of Medicine and a residency in Internal Medicine – Pediatrics at Yale. Following his residency, he completed a Clinical Informatics fellowship accredited by the ACGME in the Yale/VA program and a postdoctoral fellowship in the VA Biomedical Informatics program. As an instructor in the Department of Biomedical Informatics and Data Science and the Department of Pediatrics, he leads the Loza Lab, which focuses on the development of statistical deep learning methods to leverage Real-World Data for improving clinical care, particularly through multimodal medical foundation models.
Administered via the Graduate School of Arts and Sciences (GSAS). GRE General is optional for PhD.