About

I am a Courant Instructor at the Courant Institute of Mathematical Sciences at New York University, where I am affiliated with the NYU Simons Center for Computational Geophysical Flows. My research interests lie in data assimilation, inverse problems, and scientific machine learning. Broadly speaking, my work focuses on the design and mathematical analysis of probabilistic and data-driven methods for large-scale problems, particularly those arising in weather and climate science.

I received my PhD in Computational and Applied Mathematics at the University of Chicago in 2026, where I was fortunate to be advised by Daniel Sanz-Alonso. I completed my BS in Applied Mathematics at Case Western Reserve University in 2021.

Recent News

• 06/2026: I am speaking at a Special CMX Seminar at Caltech.

• 04/2026: I have defended my dissertation! Thanks to everyone for the support!

• 03/2026: I am speaking in MS15: Bridging Theory and Learning for Improved Bayesian Filtering at the SIAM Conference on Uncertainty Quantification.

• 11/2025: I was selected for the Rising Stars in Data Science workshop, which will take place at Stanford University November 11-12.

• 10/2025: I will give an invited talk at the John Reinitz Memorial Lecture on October 23rd.