Yao Xiao
Software Engineer
Summary
🤩
RockstarYao Xiao is a software engineer with a strong academic foundation (MS in CSE, Harvard SEAS; BS in Honors Math & CS, NYU Shanghai) and three years of hands-on experience contributing to major Python data and ML libraries. As a scikit-learn core developer and active contributor to pandas, Yao focuses on bug fixes, user-facing improvements, and robust testing—work that spans isolation forest fixes, feature selection stability, ROC visualization, and complex DataFrame merge/groupby behaviors. They combine rigorous algorithmic thinking from a math background with practical engineering skills to improve error messages, parameter validation, and developer ergonomics. Comfortable navigating both ML model internals and data-manipulation edge cases, Yao brings a developer-first perspective to open-source tooling used widely in data science.
3 years of coding experience
Github Skills (12)
data-analysis10
testing10
scikit10
pandas10
debug10
machine-learning10
pytest10
python10
scikit-learn10
data-science9
documentation9
numpy7
Programming languages (9)
Github contributions (5)
scikit-learn/scikit-learn
Mar 2023 - Mar 2025
scikit-learn: machine learning in Python
Role in this project:
Data Scientist
Data ScientistContributions:249 reviews, 163 PRs, 32 pushes in 2 years
Contributions summary:Yao contributed to fixing a warning related to feature names in the IsolationForest, a machine learning algorithm for outlier detection. Additionally, the user addressed an issue where SequentialFeatureSelector was throwing an IndexError when the cross-validation parameter was a generator. Furthermore, they added functionality to the RocCurveDisplay for plotting the chance level, and improved documentation including parameter validations and removing blockquotes. The work primarily involved modifying existing code and adding tests, demonstrating proficiency in both code maintenance and documentation.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
pandas-dev/pandas
Mar 2023 - Dec 2023
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:Data Scientist
Data ScientistContributions:33 reviews, 29 PRs, 123 comments in 9 months
Contributions summary:Yao primarily contributed to bug fixes and enhancements within the pandas library, specifically focusing on data analysis and manipulation aspects. Their work involved addressing issues related to merging dataframes, multi-index display, and group-by operations, including quantile calculation. They also implemented changes to improve error messages and deprecated keywords, indicating a focus on improving the user experience and library functionality.
pythondatalabeled-datamanipulationdataframes
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