David Sontag is an Assistant Professor of Computer Science and Data Science at NYU. Computer Science is part of the Courant Institute of Mathematical Sciences. His research focuses on machine learning and probabilistic inference, with a particular focus on applications to clinical medicine. For example, he is developing algorithms to learn probabilistic models for medical diagnosis directly from unstructured clinical data, automatically discovering and predicting latent (hidden) variables. Prof. Sontag collaborates with the Emergency Medicine Informatics Research Lab at Beth Israel Deaconess Medical Center and with Independence Blue Cross.
Previously, he was a post-doc at Microsoft Research New England. His Ph.D. is in Computer Science from MIT, where he worked with Tommi Jaakkola on approximate inference and learning in probabilistic models. Prof. Sontag received a bachelors degree from UC Berkeley in Computer Science, where he worked with Stuart Russell's First-Order Probabilistic Logic group.