Harrison Grodin
Head Teaching Assistant at University of Maryland Center for Translational Medicine
Pittsburgh, Pennsylvania, United States
Summary
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Rockstar🎓
Top SchoolHarrison Grodin is a software engineer and PhD student in programming languages at Carnegie Mellon University with nine years of engineering and teaching experience. As Head Teaching Assistant at CMU, he blends curriculum development, course infrastructure automation, and hands-on mentorship for rigorous CS courses. His open-source work includes substantive back-end refactors to ModelingToolkit.jl—an influential SciML project—and quality-focused test contributions to the Julia language itself, demonstrating deep expertise in symbolic systems and language tooling. He also built a symbolic intermediate representation and compiler for predictive healthcare analytics, bridging research-grade modeling with numerical solver targets. Comfortable operating at the intersection of research, teaching, and production code, Harrison brings a pragmatic focus on maintainability and performance to complex mathematical software.
9 years of coding experience
High School Diploma, High School Diploma at Winchester Thurston SchoolBachelor's degree, Computer Science, Bachelor's degree, Computer Science at Carnegie Mellon University
English
Stackoverflow
2,283reputation
87kreached
28answers
14questions
julia
top-5%
Github Skills (16)
computer-algebra10
differential-equations10
symbolic-computation10
julia10
test-automation10
testing10
repr9
replit9
programming-language8
vector6
plot6
python6
vectorization6
dataframe6
system-information6
Programming languages (15)
Github contributions (5)
SciML/ModelingToolkit.jl
Dec 2018 - Sep 2019
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Role in this project:
Back-end Developer
Back-end DeveloperContributions:121 commits, 26 PRs, 67 pushes in 8 months
Contributions summary:Harrison primarily focused on refactoring and extending the mathematical modeling framework within the repository. They made substantial changes to the core operator and derivative functionalities by turning the `Differential` into a higher-order function. The user's contributions include simplifying constant expressions, optimizing code indentation, and resolving subtyping issues. They also revamped and modernized the codebase for improved performance and compatibility.
sdescientific-machine-learningtransformationspartial-differential-equationsdifferential
JuliaLang/julia
Jun 2017 - Dec 2018
The Julia Programming Language
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:9 commits, 8 PRs, 21 comments in 1 year 6 months
Contributions summary:Harrison's commits primarily involve modifying and adding tests within the Julia programming language repository. They focused on refactoring existing tests for tuples, creating and updating tests related to command-line arguments, and ensuring the correct behavior of the REPL. Furthermore, the user addressed issues related to path completion within the REPL and fixed a broadcast style resolution docstring. These contributions are crucial for maintaining the quality and functionality of the Julia language.
sciencejulia-languagemachine-learningjulialangpetsc
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