Santiago Romero-Brufau, MD, PhD

Dr. Romero-Brufau uses a pragmatic combination of systems engineering, data science and machine learning operationalization (MLOps) to bridge the gap from model development to clinical impact. He is particularly interested in developing best practices that lead to better translation of models from the lab into clinical practice. He is an adjunct assistant professor in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. There he teaches two core courses for the Health Data Science Master's Program: one on deep learning and another covering the implementation of data science solutions into clinical practice.