Arjun Savel
Graduate Student
Hyattsville, Maryland, United States
Summary
👤
Senior🎓
Top SchoolArjun Savel is a PhD candidate in Astronomy at the University of Maryland, College Park, specializing in the theory and modeling of exoplanet atmospheres with eight years of research and software development experience. He combines rigorous astrophysics training from UC Berkeley and UMD with hands-on numerical and back-end coding skills, having contributed to high-profile open-source simulation work such as the TARDIS supernova radiative transfer code. His contributions include modernizing Python 3 compatibility, improving Monte Carlo and relativistic calculation reliability, and strengthening reproducibility through careful seeding and refactoring. Based in Hyattsville, Maryland, Arjun pairs deep theoretical insight with practical computational improvements that accelerate complex atmospheric modeling. Colleagues describe him as a meticulous problem-solver who bridges domain science and robust software engineering to deliver reproducible, high-fidelity simulations.
8 years of coding experience
Bachelor of Arts - BA, Astrophysics, Physics, Bachelor of Arts - BA, Astrophysics, Physics at University of California, BerkeleyDoctor of Philosophy - PhD, Astronomy, Doctor of Philosophy - PhD, Astronomy at University of MarylandHigh School, International Baccalaureate Diploma Program, High School, International Baccalaureate Diploma Program at Andrew P. Hill High
English, Spanish, Hindi
Github Skills (9)
simulations10
simulation10
numba10
supernova10
monte-carlo10
python10
astrophysics10
scientific-computing10
documentation8
Programming languages (7)
Github contributions (5)
tardis-sn/tardis
Apr 2020 - Nov 2020
TARDIS - Temperature And Radiative Diffusion In Supernovae
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 reviews, 15 commits, 21 PRs in 6 months
Contributions summary:Arjun primarily contributed to the codebase by modifying and improving the existing code related to the TARDIS supernova simulation project. Their work included refactoring the code to be compatible with Python 3 and making adjustments for consistency in documentation. They also debugged and enhanced the numerical Monte Carlo simulation aspects of the project, particularly those related to relativistic calculations, by modifying function arguments and ensuring the correct seed usage.
pythonscienceastrophysicssupernovasupernovae
arjunsavel/SImMER
Mar 2020 - Dec 2022
An open-source & modular reduction pipeline for astronomical images of point sources.
Contributions:21 releases, 2 reviews, 378 commits in 2 years 9 months
pythonpipelineastronomical-imagesastrophysicspoint
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