Summary
Kevin Gullikson is a machine learning researcher and data scientist with a PhD in Astronomy & Astrophysics and over a decade of experience turning noisy, real-world data into robust statistical models. He combines astrophysical expertise in data reduction and signal extraction with production-grade Python engineering (numpy/scipy/pandas, C/Cython, Linux) to build reproducible, open-source tools—most notably a telluric absorption modeling package used by the astronomy community. At industry roles including Staff Data Scientist at SparkCognition and currently at Trase, he applies Bayesian inference, regression, and classification methods to complex applied problems. Kevin also publishes accessible writing on data modeling outside academia, reflecting a knack for translating technical methods into practical insights.
12 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD Astronomy and Astrophysics, Doctor of Philosophy - PhD Astronomy and Astrophysics at The University of Texas at Austin
B.S. Physics, B.S. Physics at Illinois Institute of Technology
English