Kelsey DiPietro


1.  What interested you in the doctoral program in Applied and Computational Mathematics and Statistics at Notre Dame?

I was drawn by the interdisciplinary nature of the department and its focus on the computational mathematics. I also was interested in the variety of applications that the professors in the department were working on. When I came to visit the department, I was struck by how welcome I felt by both the faculty and the current doctoral students. I had come from a larger research institution, so it was nice to be in a smaller department that was easier to navigate and build relationships with faculty and other students.

2.  What was the best part of the program?

I really enjoyed the fact that I had the flexibility to pursue my interests and build a path to a career after graduation. Being able to take summer internships and participate in industry bootcamps allowed me to discern if I wanted an industrial, academic, or government position after graduating. I also appreciated the fact that being at Notre Dame gave me access to leadership development programs that have made me a better researcher and more competitive job candidate.

3.  Tell us about your doctoral thesis.

My thesis focused on creating adaptive meshing algorithms for numerically solving partial differential equations. The problem motivation came from wanting to accurately simulate a specific engineering system, but it expanded to wider classes of partial differential equations as well. We were able to create a fast, accurate algorithm for adaptive meshing algorithms using finite difference methods that can be written in a couple hundred lines of code. We have open source code on github, written in such a way that non-experts in mesh adaptation could use it for their problems.

4.  What are you working on now?

I have been working on expanding our adaptive algorithms for singularity problems for the nonlinear Schrodinger equation. In addition, I am working on implementing adaptive meshing algorithms to PDE constrained optimization problems, as well as writing a code base for our algorithm in parallel and other (more general) programming languages.

5.  How did the program prepare you for your career?

The program not only built my research skills, but helped me developed other integral skills. Access to various funding resources at Notre Dame allowed me to attend several conferences and workshops which allowed me to build my network and become comfortable presenting my work. Participating in leadership workshops built my confidence and taught me how to present my work to a broader scientific audience.

6.  What are your career plans for the near future?

I will continue during research as the Jill Hruby Postdoctoral Fellow at Sandia National Laboratory. This 3 year appointment not only allows me to build my research career, but also gives me the opportunity to participate in leadership development programs.

7.  What advice would you give to students considering the program?
Definitely make sure that there are a few faculty members who do research that you are interested in. Even if you don't understand what their recent papers are saying at a high level, its important that you find the topics exciting and could see yourself working on them for several years. I highly recommend trying to visit, it's way easier to feel out whether a place feels right once you visit.