Summary
Earl Bellinger is an assistant professor and computational astrophysicist with 12 years of experience bridging stellar astrophysics, asteroseismology, and machine learning. He combines rigorous PhD training in computer science and astrophysics with postdoctoral research at leading institutes (Max Planck, Stellar Astrophysics Centre) to develop statistical and automated-computing approaches for probing stellar evolution and variable stars. Known on GitHub as a "computational stargazer," he builds reproducible scientific software and applies modern ML and applied statistics to extract physical insight from time-series and seismic data. Based in New Haven, he blends deep technical fluency with interests in the philosophy and history of science, reflecting a reflective, systems-level approach to complex research problems.
12 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science / Astrophysics, magna cum laude, Doctor of Philosophy (Ph.D.), Computer Science / Astrophysics, magna cum laude at International Max Planck Research School for Solar System Science / University of Göttingen / Yale University
Master’s Degree, Computer Science, 3.95/4.0, Master’s Degree, Computer Science, 3.95/4.0 at Indiana University Bloomington
Dual B.Sc., Computer Science, Applied Mathematics, 3.81/4.0 (summa cum laude), Dual B.Sc., Computer Science, Applied Mathematics, 3.81/4.0 (summa cum laude) at State University of New York at Oswego
English, Portuguese, Spanish, German, r, python, bash, latex