We are the reliable Artificial Intelligence for Health and Medicine (reAIM) lab, led by Professor Shalmali Joshi in the Department of Biomedical Informatics (DBMI) at Columbia University in the City of New York.

Our vision is to design AI and ML systems to improve scientific inference and predictive capabilities in the biomedical sciences, discovery, and informatics, focused on challenges of generalizability, reliability, and robustness of inference and prediction. We develop methods that cut across deep learning, reinforcement learning, observational causal inference, and probabilistic modeling.

Find out more about our research, group, and publications.

News!

• [May 2025]: New Preprint!
  • We benchmarked SOTA structured EHR foundation models on Columbia University Medical Center data. Read more here!
• [November 2024]: [New JAMIA Perspective Published!]
  • Our perspective white paper from MLHC 2023 pre-conference workshop on “Causal Inference and Machine Learning in Healthcare” has been accepted for publication at JAMIA!