I am a Research Scientist on the Applied Team at Sakana AI. I develop reliable AI agents for enterprise financial applications. Previously, I earned a Ph.D. in Data Science at the NYU Center for Data Science, where I was advised by Kyunghyun Cho and Krzysztof Geras. I worked on detecting and mitigating spurious correlations in real-world data, primarily in the medical and biological domains.

News
Mar. 17, 2025: I defended my Ph.D. at the NYU Center for Data Science.

Mar. 3, 2025: I joined Sakana AI as a Research Scientist on the Applied Team.

Sep. 25, 2024: “Jointly modeling inter- & intra-modality dependencies for multi-modal learning” was accepted to NeurIPS 2024.

Apr. 22, 2024: I am interning with the Regev lab at Genentech to work on causal representation learning.

Aug. 29, 2023: “Detecting incidental correlation in multimodal learning via latent variable modeling” was accepted to TMLR.

May 8, 2023: I am interning with the Prescient Design group at Genentech to work on causal representation learning.

Sep. 14, 2022: “Generative multitask learning mitigates target-causing confounding” was accepted to NeurIPS 2022.