Jie Zhu
Senior Applied Scientist at Microsoft
Bellevue, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolJie Zhu is a Senior Applied Scientist with 11 years of experience applying machine learning, data mining and DBMS expertise to drive production-grade solutions at Microsoft. He holds a PhD in Atmospheric, Oceanic and Space Sciences and began his career blending geophysics and data-driven research at the University of Michigan, giving him a strong quantitative and scientific modeling background. At Microsoft he pairs rigorous research instincts with practical engineering—evidenced by contributions to the Microsoft Cognitive Toolkit (CNTK), where he implemented and debugged low-level operations like the "straight through" unary op and its Python bindings. Goal-oriented and self-motivated, Jie is as comfortable optimizing back-end computation graphs as he is communicating insights to cross-functional teams. Based in Bellevue, WA, he brings a rare mix of domain science, ML systems development, and production engineering.
11 years of coding experience
Doctor of Philosophy (PhD), Atmospheric, Oceanic and Space Sciences, Doctor of Philosophy (PhD), Atmospheric, Oceanic and Space Sciences at University of MichiganBachelor of Science (B.S.), Geophysics, Bachelor of Science (B.S.), Geophysics at University of Science and Technology of China
Github Skills (12)
neural-network10
machine-learning10
deeplearning-ai10
c-language10
cntk10
deep-learning10
cpp10
cprogramming-language10
cplus10
python9
csharp6
dotnet-core6
Programming languages (1)
Github contributions (5)
microsoft/CNTK
Apr 2016 - Sep 2018
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Role in this project:
ML Engineer
ML EngineerContributions:136 commits, 84 pushes, 77 branches in 2 years 4 months
Contributions summary:Jie primarily contributed to the implementation and refinement of the "straight through" operation within the CNTK deep learning toolkit. Their work included adding the "straight through" unary operation, fixing bugs related to its backward propagation, and adjusting the Python bindings. These changes involved modifying core math and computation network files and updating related definitions.
pytorchpythondeep-learningc-plus-plusmachine-learning
jaurora/Leetcode
Mar 2015 - Aug 2015
Contributions:186 pushes, 1 branch in 5 months
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