About Me

I'm Shane O'Brien, a physics graduate from the University of California, Irvine with a strong foundation in data analysis, scientific computing, and statistical modeling. My primary research focus has been in observational astrophysics, where I apply data science techniques (such as time-series analysis, signal extraction, and Bayesian inference) to the study of planets beyond our solar system.

I currently work with the Robertson Research Group at UC Irvine and the GEMS (Giant Exoplanets around M-dwarf Stars) Collaboration, where I am co-leading a project in the confirmation of TOI-5916b and TOI-6158b as exoplanets. This involves analyzing large datasets from space and ground-based telescopes, modeling orbital dynamics, and using probabilistic programming (e.g., MCMC sampling) to validate planetary signals. The results of this work will soon be published in the AAS Journals.

I'm now looking to pivot into a data science role where I can apply the same analytical rigor, coding skills, and statistical modeling techniques I've used in astrophysics to solve real-world problems. With hands-on experience in Python, Bayesian inference, and working with large datasets, I'm excited to bring a research-driven mindset to data-driven industries. I’m especially interested in roles that value curiosity, creative problem-solving, and a strong foundation in scientific methodology.