Michael Gully-Santiago is a Director of Applied Science in Austin with 12 years of experience turning high-resolution spectroscopic and atmospheric data into reliable, decision-ready inferences for climate mitigation and astronomy. Trained as an astrophysicist (PhD, UT Austin) and a former NASA GSRP fellow at JPL, he blends machine learning, physics-based modeling, and probabilistic inference to extract signals from noisy, biased data. At SeekOps he leads cross-functional applied science across product, software, and hardware to produce reconciliation-ready methane measurements, and earlier work supported Kepler/K2 and the Kavli Institute on exoplanet and stellar atmospheres. He favors ML architectures that encode physical structure for better interpretability and robustness, and contributes to open-source tools such as the widely used lightkurve project by improving documentation and tutorials. Motivated by deploying trustworthy systems in high-stakes settings, he bridges deep scientific expertise with production-ready engineering.
12 years of coding experience
12 years of employment as a software developer
PhD, Astronomy, PhD, Astronomy at The University of Texas at Austin
Bachelor of Arts (B.A.), Astronomy & Physics, Bachelor of Arts (B.A.), Astronomy & Physics at Boston University
A friendly package for Kepler & TESS time series analysis in Python.
Role in this project:
Technical Writer
Contributions:1 release, 43 commits, 44 PRs in 1 year 11 months
Contributions summary:Michael's contributions primarily involve creating and updating documentation files within the repository. Their commits demonstrate the addition of a page listing community software, restructuring existing documentation, renaming titles, and updating installation instructions and the developer guide. The user also made revisions to several tutorials, demonstrating a focus on improving the clarity, completeness, and usability of the documentation.
Contributions:270 commits, 4 pushes in 1 year 3 months
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Michael Gully-santiago - Environmental Data Scientist