Ye Wang
Software Engineer at microsoft
San Jose, California, United States
Summary
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RockstarYe Wang is a software engineer with six years of experience focused on machine learning infrastructure and runtime performance, currently at Microsoft in San Jose. He contributes to high-profile open-source projects such as ML.NET and ONNX Runtime, where he has improved hashing estimators, enabled ONNX conversion paths, and implemented new featurizer kernels for forecasting and rotary embeddings. Ye blends practical ML engineering with systems-level work—refactoring tests, upgrading dependencies, and adding operators that extend inference capabilities. Comfortable working across code, tests, and cross-repo integrations, he brings a pragmatic drive to make ML pipelines more robust and production-ready.
6 years of coding experience
Github Skills (17)
algorithms10
c-language10
mldotnet10
net10
machine-learning10
dotnet10
onnx10
asp-net10
mlnet10
dotnet-core10
cuda10
cprogramming-language10
csharp10
artificial-intelligence9
pytorch9
Programming languages (4)
Github contributions (5)
microsoft/onnxruntime
Mar 2020 - Jan 2023
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 676 reviews, 340 commits in 2 years 10 months
Contributions summary:Ye primarily contributed to the `microsoft/onnxruntime` repository by implementing and integrating new featurizer kernels for the ONNX Runtime. Their work involved adding operators for tasks such as short grain dropping, forecasting pivot, and rotary embeddings, as well as refactoring existing kernels. The contributions included modifying test files, creating new kernels for various operations, and updating internal dependencies, demonstrating a focus on extending ONNX Runtime's capabilities in machine learning and data processing.
runtimetrainingtensorflowai-frameworkaccelerator
dotnet/machinelearning
May 2020 - Jul 2020
ML.NET is an open source and cross-platform machine learning framework for .NET.
Role in this project:ML Engineer
ML EngineerContributions:10 commits, 25 PRs, 8 pushes in 1 month
Contributions summary:Ye primarily focused on improving the `HashEstimator` within the ML.NET framework. Their commits included supporting more data types for the hash estimator, fixing bugs, and refactoring tests. They also upgraded the code to use a newer version of the `ORT` library and resolved conflicts. The user also made changes to support ONNX conversion.
machine-learning-platformdotnetml-netmachine-learningcsharp
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