Li-wei H. Lehman

Research Scientist. massachusetts institute of technology
E25-505 · 77 Massachusetts Ave. · Cambridge, MA 02139 · LILEHMAN <at>MIT.EDU · twitter: @liwei_lehman

I am a Research Scientist at the Institute for Medical Engineering & Science (IMES), MIT. I am a Principal Investigator and lead the project on "Learning Optimal Dynamic Treatment Strategies from Temporal ICU Monitoring Data." My research focuses on machine intelligence for health, state space modeling of physiological dynamics, dynamic treatment regimes for sequential treatment decision making, or more generally, the use of machine learning to derive insights from physiological and clinical data for informed treatment decision making. My interests include generative latent variable models, switching state-space models, representation learning, Bayesian non-parametric learning of disease phenotypes, off-policy reinforcement learning, and dynamic treatment regimes. I received my Master’s degree in Computer Science from Georgia Institute of Technology, and my Ph.D. from Massachusetts Institute of Technology in 2005.

Research positions available: I am looking for highly-motivated Research Interns (graduate level), Research Fellows, and Post-Docs to join my research team starting immediately. For more details, see here.


Selected Publications

Switching State-Space Approaches for Modeling Physiological Dynamics

Representation Learning from Physiological and Clinical Data

Machine Learning and Causal Inference for Informed Clinical Sequential Decision Making

Deriving Insights from Clinical Text: Bayesian Non-parametric Learning of Patient Phenotypes

Electronic Health Records and Medical Informatics

All Publications (By Year)

2019 - Present









Professional Activities and Honors

  • Distinguished Paper Award, AMIA Annual Symposium, 2020.
  • Program Committee member: Thirty-Fourth AAAI Conference on Artificial Intelligence, 2019-2020.
  • Organizing Committee, The second NorthEast Computational Health Summit (NECHS) – AI in Healthcare, MIT-IBM Watson AI Lab, Cambridge, MA, April 27, 2018.
  • Guest Editorial Board member, Nature Scientific Data, 2017.
  • Organizing committee, the PhysioNet/Computing in Cardiology Challenge, 2017 - 2018.
  • Organizer, Symposium, "Data-driven Learning, Discovery, and Innovation" at 2014 Computing in Cardiology Conference, MIT Media Lab, Cambridge MA, September 2014.
  • Co-organizer, the 10th Annual PhysioNet/Computers in Cardiology Challenge “Predicting acute hypotensive episodes,” 2009.
  • Local organizing committee, the 41st Annual International Conference of Computing in Cardiology, Cambridge, MA, September 7-10, 2014.
  • Best poster presentation award in 2007 Computers in Cardiology Conference.
  • Schoettler Fellowship, awarded to outstanding graduate students, MIT.