Bio

I’m a 4th year Mathematics Ph.D. student at UCLA, supported by the NSF Graduate Research Fellowship and advised by Andrea Bertozzi. My recent research is in deep learning and graph-based semisupervised learning theory and algorithms, and their applications to both remote and quantum sensing. In particular, I’m interested in environmental and climate-focused applications.

In Summer 2024, I was a research intern at NASA Jet Propulsion Lab, building a transformer-based model for damage mapping after natural disasters (landslides, fires, floods) with global synthetic aperture radar (SAR) data. I was mentored by Charlie Marshak and Al Handwerger. You can see an application of my work to the recent LA fires on the NASA Disasters website.

For undergrad I went to Tufts University, graduating Summa Cum Laude with degrees in Mathematics and Mechanical Engineering and was a Captain on the Varsity Rowing Team. I was advised by James Murphy.

I am looking for research/applied scientist internship roles for Summer 2025. Feel free to contact me via the sidebar to the left.

News

3/2025: Our paper Deep Self-Supervised Disturbance Mapping with the OPERA Sentinel-1 Radiometric Terrain Corrected SAR Backscatter Product was accepted to IEEE JSTARS! This paper covers the work I did during my internship at JPL.

12/2024: A preprint of our paper, GLL: A Differentiable Graph Learning Layer for Neural Networks is available on Arxiv. This paper derives a new methodology for backpropagating through a general family of graph learning equations and uses these insights to design a novel “Graph Learning Layer” (GLL).

11/2024: I passed my Oral Qualifying Exam and Advanced To PhD Candidacy! Thank you to my committee members: Andrea Bertozzi, Jeff Calder, Deanna Needell, and Hayden Schaeffer.

08/2024: I presented a poster at the Science Understanding Through Data Science Conference at Caltech.

07/2024: This summer, I’m interning at NASA JPL!

09/2023: We had a paper accepted to IEEE WHISPERS!

03/2023: This quarter I am TAing for Math 33A (Linear Algebra) and 33B (Differential Equations).

03/2023: I recieved the National Defense Science and Engineering Graduate (NDSEG) Fellowship!

03/2023: I recieved the National Science Foundation Graduate Research Fellowship!

03/2023: I ran the LA Marathon in 3:53:25!

01/2023: My paper, “Deep Semi-supervised Label Propagation for SAR Image Classification” was accepted to the SPIE Conference on Defense and Remote Sensing! I am co-first author, and was lucky to be able to collaborate with Joshua Enwright (UCLA, co-first author), Jeff Calder (UMN), and Andrea Bertozzi (UCLA).

01/2023: This quarter I am TAing for Math 31B (Integration and Infinite Series).

03/2022: I passed the Numerical Analysis and “Basic” Qualifying Exams, so I’ve completed my written Qualifying Exam requirements!

12/2021: I passed the Optimization/Numerical Linear Algebra Qualifying Exam!

09/2021: I started as a PhD student at UCLA! For my first year, I am fortunate to be supported by an NSF NRT MENTOR Fellowship.

Hobbies/Personal

I was a rower in high school and college and have continued to do endurance sports since then. Now I enjoy training for marathons, cycling, and hope to start doing triathlons soon. I’m also a huge sports fan, including the NBA, NFL, college basketball and football, soccer, and pro cycling.