Adam Ginsburg is an associate professor and astrophysicist with 16 years of experience bridging research and open-source software development from Gainesville, Florida. He develops and documents scientific Python libraries widely used in astronomy—contributing notable features such as an FFT-based convolution to Astropy and backend fixes to astroquery and yt that improve FITS handling and data exports. His work spans visualization and data-science tooling in projects like glue, where he enhanced multi-layer workflows, and he brings a practiced eye for documentation and reproducible tutorials in astropy-tutorials. Combining academic leadership at the University of Florida with prior fellowships at NRAO and ESO, he specializes in turning complex observational data formats into robust, user-friendly tools. A not-obvious strength is his consistent focus on both code correctness and end-user clarity, from low-level URL parsing to polished tutorial content.
16 years of coding experience
5 years of employment as a software developer
Bachelor of Science, Astrophysics, Bachelor of Science, Astrophysics at Rice University
PhD, Astrophysics, PhD, Astrophysics at University of Colorado Boulder
Functions and classes to access online data resources. Maintainers: @keflavich and @bsipocz
Role in this project:
Back-end Developer
Contributions:13 releases, 463 reviews, 2492 commits in 10 years 8 months
Contributions summary:Adam primarily made changes to the core code of the astroquery library, specifically in the `alma` module. The changes involved fixing bugs in URL constructions, refactoring to allow for different return types, and updating tests to reflect changes in the ALMA archive. The user also introduced a utility for parsing the frequency support section of ALMA tables.
Contributions:61 reviews, 432 commits, 64 PRs in 10 years
Contributions summary:Adam implemented a new function (`convolve_fft`) for performing convolutions using FFT, contributing significant functionality to the library. The user's work involved writing new code, restructuring existing functions, and addressing code efficiency, as well as fixing bugs and implementing parameter validation. Additionally, the user significantly improved the documentation and added examples to make the functions easier to use.
core-librarypythonastronomyscienceastrophysics
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