Cha Zhang
Research Scientist at Microsoft Research
Redmond, Washington, United States
Summary
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RockstarCha Zhang is a Research Scientist based in Redmond with a decade of experience building robust back-end systems for machine learning tooling. As a principal researcher-level contributor to Microsoft Cognitive Toolkit (CNTK), Cha improved core image-reading functionality—fixing grayscale handling and addressing cross-platform compilation and ZipByteReader bugs—demonstrating attention to production-quality data pipelines. Comfortable bridging research and engineering, Cha focuses on dependable data ingestion and preprocessing for deep learning workloads. Colleagues value a pragmatic problem-solver who surfaces subtle edge cases in large codebases and ships reliable fixes that improve downstream model training.
10 years of coding experience
English, Chinese
Github Skills (10)
c-language10
cprogramming-language10
image-processing10
fileio9
file-access9
file-handling9
file-processing9
computer-vision9
cudnn8
deep-learning7
Programming languages (4)
Github contributions (5)
microsoft/CNTK
Apr 2016 - Nov 2017
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Role in this project:
Back-end Developer
Back-end DeveloperContributions:280 commits, 40 PRs, 386 pushes in 1 year 7 months
Contributions summary:Cha's contributions primarily focused on modifying and improving the image reader functionality within the Microsoft Cognitive Toolkit (CNTK). They addressed issues related to grayscale image processing, including fixing the ImageReader to correctly handle grayscale images. They also worked on enhancing image reading capabilities, including resolving bugs in the ZipByteReader and implementing solutions for handling potential compilation errors on Linux systems.
pytorchpythondeep-learningc-plus-plusmachine-learning
microsoft/FERPlus
Sep 2016 - Sep 2016
This is the FER+ new label annotations for the Emotion FER dataset.
Contributions:8 commits, 2 comments in 1 day
ferdatasetemotionannotations
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