David Sontag's Home Page

E-mail: dsontag {@ | at} mit.edu

Clinical machine learning group website

I am an Associate Professor of Electrical Engineering and Computer Science at MIT, part of both the Institute for Medical Engineering & Science and the Computer Science and Artificial Intelligence Laboratory. My research focuses on advancing machine learning and artificial intelligence, and using these to transform health care. Previously, I was an Assistant Professor of Computer Science and Data Science at New York University, part of the CILVR lab.



Spring '17, '19, '20, '21: Machine Learning for Healthcare (6.871, HST.956)
Fall 2017, 2018, 2019: Machine Learning (6.867)
Fall 2016: Inference and Representation (DS-GA-1005 and CSCI-GA.2569)
Spring 2016: Introduction to Machine Learning (CSCI-UA.0480-007)


All publications


Download Python code for learning topic models (corresponds to ICML '13 paper). See also David Mimno's Mallet-compatible Java implementation.
Download code for learning Bayesian network structure (corresponds to UAI '13 SparsityBoost paper).
Download C++ code for MAP inference in graphical models (corresponds to UAI '12 paper; see readme file).
Low-dimensional embeddings of medical concepts (corresponds to AMIA CRI '16 paper)
DeepDiagnosis from longitudinal clinical data (corresponds to MLHC '16 paper)

MIT Accessibility