Xiaoying Wang
Researcher at Microsoft
Redmond, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolXiaoying Wang is a researcher and software engineer with 11 years of experience building high-performance backend systems and data tooling, currently at Microsoft in Redmond. She blends production-grade experience from developing low-latency, high-concurrency ad-exchange services at Qihoo 360 with academic rigor from a PhD track in Computer Science at Simon Fraser University. Her open-source contributions include enhancing Connector-X—the fastest DB-to-DataFrame loader—and integrating it into Dataprep, improving CSV handling, SQL read paths, tests, and documentation. Xiaoying focuses on practical robustness: parsing tricky data types, adding comprehensive tests, and smoothing developer experiences across Python and Rust boundaries. Colleagues would describe her as a pragmatic engineer who moves fluently between research prototypes and production APIs. She brings a rare combination of systems performance tuning, data engineering, and reproducible research practices to applied data problems.
11 years of coding experience
2 years of employment as a software developer
Bachelor's degree Computer Software Engineering, Bachelor's degree Computer Software Engineering at Tongji UniversityDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Simon Fraser University
Github Skills (15)
csv-parsing10
data-preprocessing10
csv-parse10
rust10
dataprep10
database-connection10
sql10
python10
data-engineering10
pytest9
testing9
datatypes9
unit-testing9
api8
documentation8
Programming languages (11)
Github contributions (5)
sfu-db/connector-x
Jan 2021 - Jan 2023
Fastest library to load data from DB to DataFrames in Rust and Python
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:10 releases, 49 reviews, 962 commits in 2 years
Contributions summary:Xiaoying implemented new functionality for interacting with CSV data sources within the "connector-x" library. Their contributions included initializing a CSV source, running queries, and producing results from the CSV data. Additionally, they added several tests related to loading, parsing and writing data from CSV files, and ensured the library can correctly parse and handle different data types, including optionals. They also worked on enhancements and integration of external libraries to implement these features effectively.
polarspythondataframesdataframerust
sfu-db/dataprep
Oct 2021 - Nov 2021
Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.
Role in this project:Backend Developer
Backend DeveloperContributions:1 release, 11 commits, 2 PRs in 1 month
Contributions summary:Xiaoying primarily focused on integrating the `connectorx` library for database connectivity within the `dataprep` library. This involved adding functionality to read data from SQL databases using the `read_sql` function, and creating associated tests and documentation. The user also updated documentation examples and corrected hyperlinks within the documentation, showcasing a focus on practical use cases.
pythondatadataprepcleaningdatacleaning
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