Zhou Wang

Principal Software Engineer at Microsoft

Aachen, North Rhine-Westphalia, Germany
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Summary

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Rockstar
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Top School
Zhou Wang is a Principal Software Engineer with over 10 years of experience designing and delivering distributed systems, cloud services, and system-level software from architecture through release. At Microsoft he has focused on Speech Services for Azure Cognitive Services—building real-time and batch transcription pipelines and SDKs—while also contributing to core deep learning tooling such as the open-source Microsoft Cognitive Toolkit (CNTK). His background spans virtualization on ARM, trusted execution environments, hypervisor-enforced code integrity, and wireless network optimization, reflecting a blend of low-level systems expertise and cloud-scale service development. Comfortable across C++ and cross-platform build/debug challenges, he has fixed Linux compilation issues and simplified complex codepaths in performance-critical modules. Based in Aachen and holding a Dr.-Ing. in computer science from KIT, he brings research-grade rigor from his Fraunhofer years to pragmatic, production-focused engineering.
code9 years of coding experience
job3 years of employment as a software developer
bookDr.-Ing. Informatik, Dr.-Ing. Informatik at Karlsruhe Institute of Technology (KIT)
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Github Skills (12)

c-language10
deep-learning10
cprogramming-language10
platform-independent9
gd9
multiplatform9
debug9
sgd9
debugging9
cross-platform9
mpi7
linux6

Programming languages (9)

PowerShellC#TypeScriptJavaC++CObjective-CMarkdown

Github contributions (5)

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microsoft/CNTK

Jun 2016 - Dec 2017

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Role in this project:
userBack-end Developer
Contributions:573 commits, 5 PRs, 1176 pushes in 1 year 5 months
Contributions summary:Zhou addressed code review comments, simplifying and removing preprocessor directives in the CNTK codebase. They primarily modified C++ source files, specifically in the areas of Stochastic Gradient Descent and MPIWrapper, indicating a focus on improving and optimizing core deep learning code. Furthermore, the user fixed compilation errors on Linux related to the CNTK evaluation library, suggesting involvement in cross-platform development and debugging of the evaluation module.
pytorchpythondeep-learningc-plus-plusmachine-learning
singaxiong/CNTK

Nov 2016 - Dec 2016

Contributions:22 commits in 6 days
cognitive-toolkitcntkcognitivemicrosoft
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