Ryan Friedman

Postdoctoral Scholar at University of Washington

Missouri, United States
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Summary

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Senior
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Top School
Ryan Friedman is a computational biologist and postdoctoral scholar specializing in gene regulation, combining expertise in supervised and active learning, model interpretation, and sequencing-based assays such as Massively Parallel Reporter Assays. With a PhD in Computational and Systems Biology and a decade of experience spanning Washington University and the University of Washington, he builds reproducible analysis pipelines that bridge machine learning and experimental genomics. He brings domain knowledge in transcription factor biology and a practical focus on accessible, colorblind-friendly data visualization. Unusually for an academic computationalist, he pairs hands-on high-throughput sequencing pipeline development with active-learning approaches to prioritize experiments, accelerating discovery at the interface of data and wet-lab biology.
code10 years of coding experience
job2 years of employment as a software developer
bookBachelor of Arts - BA, Genomics & Computational Biology, Computer Science, 3.88, Bachelor of Arts - BA, Genomics & Computational Biology, Computer Science, 3.88 at Washington University in St. Louis
languagesEnglish, Hebrew, French
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Github Skills (16)

sequence9
deep-learning7
pytorch6
machine-learning6
conversations5
tensorflow5
github-app5
slack4
tcl-tk4
chainer3
slack-integration3
tcl2
homebrew2
multiplex1
fairness-ml1

Programming languages (4)

RShellVisual BasicJupyter Notebook

Github contributions (5)

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Contributions:18 commits, 13 pushes, 1 branch in 10 months
rfriedman22/selene

Jun 2021 - Oct 2024

a framework for training sequence-level deep learning networks
Contributions:1 release, 6 pushes, 10 branches in 3 years 5 months
pytorchsequencedeep-learningmachine-learningtraining
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Ryan Friedman - Postdoctoral Scholar at University of Washington