Camille Liotine is a Senior Data Science Engineer based in Chicago with a decade of experience bridging astrophysics research and production-grade software. With a PhD in Astronomy from Northwestern and a BA in Astrophysical Sciences from Princeton, she has led core development on the POSYDON simulation platform and translated complex models into robust, deployable code. Camille has applied machine learning to community-centered problems—spearheading a project at Northwestern’s CORNERS to evaluate violence intervention outcomes—and brings proven experience communicating technical ideas to diverse audiences, from veterans to international researchers. Now at Huski.ai, she combines deep domain expertise in computational science with practical data engineering to move research workflows into impactful products. An uncommon strength is her track record of integrating research-grade simulations into versioned, production releases, demonstrating both scientific rigor and software delivery discipline.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Astronomy and Astrophysics, Doctor of Philosophy - PhD, Astronomy and Astrophysics at Northwestern University
Bachelor of Arts (A.B.), Astrophysical Sciences, Computing, Bachelor of Arts (A.B.), Astrophysical Sciences, Computing at Princeton University
POSYDON is a next-generation single and binary-star population synthesis code incorporating full stellar structure and evolution modeling Topics Resources
Contributions:1 PR, 78 pushes, 2 branches in 1 year 8 months
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