Ryan Poplin
Principal Scientist, Health AI ML at Apple
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolRyan Poplin is a Principal Scientist focused on Health AI/ML with 11 years of experience bridging genomics, large-scale machine learning, and production engineering. He has led research and engineering teams at Google, DeepMind, and now Apple, driving projects such as DeepVariant and GATK that apply deep learning to DNA sequencing and genome analysis. Equally comfortable managing teams and diving into dependency- and build-level fixes, he has hands-on experience updating complex ML pipelines (TensorFlow, Bazel, NumPy) to keep flagship open-source tools production-ready. Trained in computational neuroscience (CMU) with a background in CS and math, he combines rigorous academic foundations with a track record of shipping robust, scientifically-grounded ML systems at scale. An understated strength is his knack for operationalizing research into maintainable engineering—ensuring models not only advance science but run reliably in real-world health settings.
11 years of coding experience
2 years of employment as a software developer
Master of Science (M.Sc.), Computational Neuroscience, Master of Science (M.Sc.), Computational Neuroscience at Carnegie Mellon UniversityBachelor of Science (B.Sc.), Computer Science and Mathematics, Bachelor of Science (B.Sc.), Computer Science and Mathematics at Rose-Hulman Institute of Technology
Github Skills (9)
tensorflow10
python10
bazel10
machine-learning9
deep-learning8
deeplearning-ai8
numpy8
bioinformatics7
gcp6
Programming languages (3)
Github contributions (5)
google/deepvariant
Dec 2017 - Sep 2018
DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 23 commits, 1 PR in 9 months
Contributions summary:Ryan primarily focused on maintaining and updating dependencies within the DeepVariant project. They updated versions of TensorFlow, Bazel, and NumPy, ensuring compatibility with user requests and the project's build process. They made changes to Python test files, and updated GPU-specific tests. Additionally, the user modified configuration files to reflect these dependency updates and adjusted the TensorFlow build process.
genomedeepvariantdnabioinformaticstensorflow
rpoplin/testing
Dec 2017 - Dec 2017
Contributions:3 pushes, 1 branch in 1 day
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.