Navid Dianati

Senior Applied Scientist at Amazon

Seattle, Washington, United States
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Summary

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Senior
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Top School
Navid Dianati is a Senior Applied Scientist in Seattle with 11 years of experience translating advanced math and physics into production-ready machine learning and data analytics for scientific discovery. With a PhD in physics and an MS in applied mathematics from the University of Michigan, he has driven cross-disciplinary projects from computational social science to large-scale drug discovery, leading the analytical phase of a Broad–Bayer partnership that triaged 100K compounds. He combines a strong theoretical background—publishing novel statistical methods—with hands-on engineering of data pipelines, anomaly detection, metric learning, and deep learning for high-throughput genomics. Comfortable moving between research and product, he excels at turning complex experimental data into mechanistic hypotheses and prioritized candidates for follow-up. Outside work he pursues algorithms, mathematical digital art and photography, reflecting a curiosity that fuels both technical depth and creative problem-solving.
code11 years of coding experience
job5 years of employment as a software developer
bookDoctor of Philosophy (Ph.D.), Physics, Doctor of Philosophy (Ph.D.), Physics at University of Michigan
languagesEnglish, Persian
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Github Skills (21)

weighted10
network-graph9
igraph9
pruning9
filter9
wolfram-language8
julia8
mathematics8
python-interface8
connectivity8
random-walk8
genetics8
network-analysis8
graph-algorithms7
complex-networks6

Programming languages (3)

CSSCPython

Github contributions (5)

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naviddianati/python-reveal

Apr 2016 - Aug 2021

Contributions:16 commits, 11 pushes, 1 branch in 5 years 5 months
naviddianati/GraphPruning

May 2015 - Aug 2021

Package for "pruning" weighted complex networks based on the Marginal Likelihood Filter.
Contributions:1 release, 30 commits, 20 pushes in 6 years 3 months
marginalpruningcomplex-networkslikelihoodjulia
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Navid Dianati - Senior Applied Scientist at Amazon