Scholar
Rajesh Ranganath
Google Scholar ID: kddKBCsAAAAJ
Assistant Professor, NYU
Citations & Impact
Citations
10,621
H-index
41
i10-index
86
Publications
20
Co-authors
0
Contact
Publications
Resume (English only)
Academic Achievements
- Published multiple papers on topics including survival mixture density networks, set norm and equivariant skip connections, out-of-distribution generalization, fast SHAP value estimation, learning invariant representations with missing data, individual treatment effect estimation, inverse-weighted survival games, offline reinforcement learning, probabilistic machine learning for healthcare, scalable set recommendation, understanding failures in out-of-distribution detection with deep generative models, offline contextual bandits, reproducibility in machine learning for health research, contrarian statistics for controlled variable selection, how interpretability methods can learn to encode predictions, a real-time prediction model for favorable outcomes in hospitalized COVID-19 patients, finding comparable cohorts in observational health data, and data-driven physiologic thresholds for iron deficiency associated with hematologic decline.
Research Experience
- Spent time as a research affiliate at MIT’s Institute for Medical Engineering and Science.
Education
- Earned a PhD from Princeton University, advised by Dave Blei; completed undergraduate studies at Stanford University.
Background
- An Assistant Professor at the Courant Institute at NYU in Computer Science and at the Center for Data Science. Research interests include causal, statistical, and probabilistic inference, out-of-distribution detection and generalization, deep generative modeling, interpretability, and machine learning for healthcare.
Co-authors