Anthony Gitter
Software Engineer
Summary
🤩
RockstarAnthony Gitter is a software engineer with a decade of experience who blends robust backend and DevOps skills with academic-driven projects in computational biology. He has contributed significant engineering work to the well-regarded greenelab/deep-review, implementing author metadata automation, CI/CD pipelines, and manuscript build tooling that streamline collaborative scientific publishing. Comfortable working at the intersection of research and production, he translates complex authorship and funding requirements into reliable automated systems. His background ties to biostatistics and medical informatics communities, reflecting an ability to collaborate with academic investigators and research institutes. Colleagues rely on him for pragmatic tooling that reduces editorial friction and improves reproducibility across large, multi-author projects.
10 years of coding experience
Github Skills (15)
python10
cicd10
build-automation10
spellchecking9
pandas9
bash8
github-ci8
jinja28
githubaction-workflow8
dockers7
docker7
documentation6
yaml6
deep-learning5
deeplearning-ai5
Programming languages (16)
Github contributions (5)
greenelab/deep-review
Oct 2016 - Dec 2021
A collaboratively written review paper on deep learning, genomics, and precision medicine
Role in this project:
Backend & DevOps Engineer
Backend & DevOps EngineerContributions:2 releases, 1 review, 356 commits in 5 years 3 months
Contributions summary:Anthony's commits primarily focus on the development and maintenance of the author ordering, author metadata, and build processes for the deep-review manuscript. They implemented author list templates, dynamically generated author counts, and standardized funding information. The user also worked on setting up and improving the continuous integration and deployment pipeline, including enabling spellchecking and deploying to gh-pages.
manubotprecision-medicinedeep-learningneural-networksmachine-learning
agitter/Machine-learning-for-proteins
May 2019 - May 2024
Listing of papers about machine learning for proteins.
Contributions:5 pushes, 5 branches in 5 years 1 month
proteinsmachine-learninglisting
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.