Chad Eliason
Machine Learning Engineer at Topstep
Chicago, Illinois, United States
Summary
👤
Senior🎓
Top SchoolChad Eliason is a machine learning engineer with 13 years of research-driven experience applying Bayesian and ML methods to large, complex biological and behavioral datasets. He has transitioned high-impact academic work into production-ready tools—building R packages (including the widely used pavo), large ETL pipelines, and a 1.3M-measurement PostgreSQL database—to enable scalable analysis across genomics, color science, and museum visitor prediction. At the Field Museum he combined social data, weather, and neural nets to improve visitor and pricing models, and his postdoctoral work used HPC and probabilistic inference to deliver orders-of-magnitude improvements in range and evolutionary predictions. A prolific contributor to peer-reviewed science (30+ papers) and creator of widely adopted research software, he blends statistical rigor with pragmatic engineering to drive data-driven decisions in fast-paced research settings.
13 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at The University of AkronBachelor of Science - BS, Biology, Bachelor of Science - BS, Biology at Baldwin Wallace University
Github Skills (1)
r9
Programming languages (2)
Github contributions (5)
celiason/phenotools
Aug 2018 - Sep 2024
Contributions:4 releases, 18 pushes, 1 branch in 6 years 1 month
celiason/celiason.github.io
Oct 2016 - Jan 2023
Contributions:178 commits, 3 PRs, 234 pushes in 6 years 4 months
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