About

This fall I am joining the Courant Institute of Mathematical Sciences at New York University as a Courant Instructor. I am interested in problems at the intersection of applied mathematics, computational science, and statistics. My work aims to combine complex physical models with data in a mathematically principled way. More concretely, my research has focused on inverse problems, data assimilation, and scientific machine learning. 

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.