Xiaoyun Zhang
Senior Software Engineer at Microsoft
Greater Seattle Area United States
Summary
🤩
Rockstar🎓
Top SchoolXiaoyun Zhang is a Senior Software Engineer based in the Greater Seattle Area with a decade of experience building backend systems and machine learning tooling at Microsoft. She has been a core contributor to ML.NET and Model-Builder, adding AutoML recommendation capabilities and practical time-series forecasting examples that help C# developers integrate trained models into production. Her open-source work includes backend enhancements to Microsoft's autogen framework for agentic AI, demonstrating a blend of ML engineering and production-grade backend development. Xiaoyun’s strengths lie in turning research-grade models into developer-friendly tools, with a strong track record of rigorous testing and integration across large-scale projects. She brings an international academic background from Xi'an Jiaotong University and an exchange stint at the National University of Singapore, reflecting both technical depth and cross-cultural collaboration. An attention to validation and developer experience—rather than just model accuracy—sets her work apart.
10 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Xi'an Jiaotong UniversityExchange student, School of Compute, 4.5/5.0, Exchange student, School of Compute, 4.5/5.0 at 新加坡国立大学
Github Skills (24)
recommendation-system10
ai-agent10
python10
mldotnet10
machine-learning10
regression10
agent10
time-series-forecasting10
mlnet10
automl10
dotnet-core10
jupyter-notebook10
csharp10
nuget9
unit-testing9
Programming languages (15)
Github contributions (5)
dotnet/machinelearning
Aug 2019 - Jan 2023
ML.NET is an open source and cross-platform machine learning framework for .NET.
Role in this project:
ML Engineer
ML EngineerContributions:308 reviews, 105 commits, 250 PRs in 3 years 5 months
Contributions summary:Xiaoyun's contributions centered around adding a recommendation task to the AutoML feature of ML.NET. They implemented the ability to train recommendation models for predicting ratings. The changes involved validating user input, especially concerning label types, and the integration of recommendation-specific functionality within the automated machine learning framework. This work included extensive unit tests validating the robustness of the newly added recommendation task.
machine-learning-platformdotnetml-netmachine-learningcsharp
microsoft/autogen
Sep 2023 - Feb 2025
A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
Role in this project:Back-end Developer
Back-end DeveloperContributions:292 reviews, 264 PRs, 539 pushes in 1 year 5 months
Contributions summary:Xiaoyun's commits primarily focused on the backend of the `autogen` repository, specifically on adding and improving the functionality of agents. The user contributed to the project by implementing a custom meta feature function and updating existing code related to the integration with other tools. The user also made changes to agent chat functionality, code utils, and test code.
agenticagentic-agiagentsaiautogen
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