Scott Coughlin is a computational specialist and lead with a decade of experience helping researchers scale scientific software on high-performance computing systems. Holding a PhD in Gravitational Wave Astrophysics from Cardiff University, he combines deep domain knowledge with practical skills in Python, C/C++, MPI/OpenMP, SQL, and containerized deployment. At Northwestern he has guided HPC adoption, created reusable optimized libraries, and taught researchers best practices from CI and unit testing to parallelization and web/database deployment. He contributes to educational open-source resources—such as SQL-focused notebooks for the LSSTC Data Science Fellowship—bridging teaching and production-ready tooling. Based in Evanston, he’s equally comfortable debugging parallel kernels or designing citizen-science data pipelines, a blend of research rigor and hands-on engineering that accelerates reproducible science.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Cardiff University / Prifysgol Caerdydd
Bachelor of Arts (B.A.) Mathematics Economics Classics, Bachelor of Arts (B.A.) Mathematics Economics Classics at Northwestern University
Lecture slides, Jupyter notebooks, and other material from the LSSTC Data Science Fellowship Program
Role in this project:
Data Scientist
Contributions:9 commits, 6 PRs in 3 days
Contributions summary:Scott's commits primarily involve modifications to a Jupyter Notebook file, "IntroductionToSQL.ipynb," which is part of the LSSTC Data Science Fellowship Program. These changes focus on introducing SQL concepts using the IMDb dataset. The user has implemented several code cells including basic data science libraries such as pandas, and also included code to connect to a PostgreSQL database, which includes a MongoDB section as well.
This repo contains code for the GravitySpy Citizen Science project.
Contributions:11 pushes, 1 branch in 3 years 7 months
citizen-sciencescience
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