Greg Fedewa is an independent contractor and computational biologist with a decade of experience building reproducible bioinformatics pipelines, large-scale metagenomic analyses, and ML models for biomarker discovery. He holds a PhD in Bioinformatics from UCSF (DeRisi lab) and applied those skills as a postdoc at Cambridge developing novel antigenic deconvolution methods for viral evolution and immune response. Greg has led pipeline and cloud infrastructure work at startups and labs—processing thousands of samples, authoring pipeline features in nf-core/mag, and contributing to grant and hiring processes. He blends wet-lab understanding (from early molecular work and viral genomics) with production-grade software practices (Nextflow, Terraform, AWS/GCS) to move projects from data to decision. Notably, he built a protein language model to predict enzyme activity and prioritized experimental variants, illustrating a rare mix of machine learning and hands-on experimental assay design. Based in the United States, he thrives at the interface of computational method development, reproducible workflows, and translational microbiome/viral research.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (PhD), Bioinformatics, Doctor of Philosophy (PhD), Bioinformatics at UCSF
B.S., Biochemistry & Molecular Biology, B.S., Biochemistry & Molecular Biology at Michigan State University
Racmacs R package for performing antigenic cartography (https://acorg.github.io/Racmacs)
Contributions:1 PR, 4 pushes, 7 branches in 3 months
r-packagerstatscartography
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.