Hello, I'm Alex Fish

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profile of alex

About Me

I am expecting to graduate with a PhD in Applied and Computational Mathematics from Southern Methodist University in May, 2023. My advisor is Daniel Reynolds and I am currently funded by FASTMath SciDAC. My research is focused on adaptivity in multirate numerical IVP-solving methods.

I am passionate about mathematics and software development with experience in industry, academia, and national labs.

I am currently looking for a post-graduation job in computational mathematics, scientific computing, machine learning, and related fields!

Professional Experience

Intern, Lawrence-Livermore National Lab

In the summer of 2022 I interned with the SUNDIALS team to optimize integrator parameters, in collaboration with the GPTune team.

Software Engineer, Northrop Grumman

From May, 2018 to June, 2020, as both intern and full software engineer, I worked with a team in an agile environment to develop software for the US Government.

Intern, InterPublic Group

In the summer of 2017 I interned with InterPublic Group, writing user-management scripts and developing tools for their global IT Support.


New Family of Numerical IVP-Solving Methods

This work is in development.

New Numerical IVP-Solving Methods in Existing Families

This work is in development.

Adaptive Time Step Control for Multirate Infinitesimal Methods

Novel time-step controllers specifically designed for multirate infinitesimal numerical IVP-solving methods leveraging techniques from Control Theory. 2022.


An Eclipse IDE plug-in to assist software engineers in managing code clones, similar segments of code within a codebase, across versions of software. 2018.


PhD, Applied and Computational Mathematics

Southern Methodist University. Expected May, 2023. Advisor: Daniel Reynolds. Thesis topic: Adaptivity in multirate numerical IVP-solving methods.

MS, Applied Mathematics

University of Washington. 2020.

BS, Mathematics with Computer Science Minor

University of Nebraska Omaha. 2019.