I am a Faculty Fellow at NYU's Center for Data Science, working on machine learning and causal inference with a focus on healthcare applications. My interests span foundational and applied questions in topics such as out-of-distribution generalization, sequential decision-making, ML safety, and probabilistic inference.
Before NYU I was a postdoctoral fellow at Johns Hopkins working with Prof. Suchi Saria. Even before that, I received my PhD at the Hebrew University under the supervision of Prof. Amir Globerson and Prof. Ami Wiesel, while working at Google Research Tel Aviv on explainability of computer vision models.
News:
Before NYU I was a postdoctoral fellow at Johns Hopkins working with Prof. Suchi Saria. Even before that, I received my PhD at the Hebrew University under the supervision of Prof. Amir Globerson and Prof. Ami Wiesel, while working at Google Research Tel Aviv on explainability of computer vision models.
News:
- In summer 2026 I'll be joining the faculty of Data and Decision Sciences at the Technion as an Assistant Professor! Please drop a line if you're a student interested in working together at the Technion or at NYU until then.
- Our paper on "scalable effect estimation for interventions on when and what to do" is accepted to ICLR25.
- Shalmali Joshi and collaborators beautifully summarized thoughts from a workshop on causality and AI in healthcare. Published now in JAMIA.
- Slides for our NeurIPS24 tutorial on Out-of-Distribution Generalization: Shortcuts, Spuriousness and Stability are available here. Thanks to the amazing Aahlad Puli and Maggie Makar for making this such a fun experience.