Rajesh Ranganath

Rajesh Ranganath is an Assistant Professor at New York University's Courant Institute of Mathematical Sciences and the Center for Data Science. He is affiliated with the CILVR group and specializes in machine learning for healthcare, probabilistic modeling, and causal inference. His research bridges theoretical advancements and practical applications in healthcare, including out-of-distribution detection, generative models, and interpretability.

Education:

• Ph.D., Computer Science, Princeton University (USA)
• B.S., Computer Science, Stanford University (USA)

Research Interests:

• Causal and probabilistic inference
• Out-of-distribution generalization
• Deep generative modeling
• Healthcare applications
• Interpretability and explainability

Awards & Recognition:

No specific awards listed in provided materials, though his work has been recognized through publications in top venues like NeurIPS, ICML, and ICLR.

Advisees & Labs:

• PhD Students: Mark Goldstein, Neil Jethani, Aahlad Puli, Adriel Saporta, Raghav Singhal
• Labs/Teams: CILVR Group, NYU Center for Data Science