Guoxin Wang
Senior Research SDE at Microsoft
Bellevue, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolGuoxin Wang is a Senior Research Software Development Engineer at Microsoft with nine years of experience building high-performance back-end systems and distributed search infrastructure. He specializes in large-scale vector search, data compression, and performance optimization—contributing to Microsoft’s SPTAG ANN library with delta-encoding, Zstandard integration, and parallelized compression to speed queries and reduce storage. Guoxin has a strong DevOps and systems background from work on cluster/resource management (PAI) and a knack for clear technical documentation demonstrated through contributions to the NNI AutoML docs. Trained in geographic information systems and cartography, he brings spatial thinking to problems in search and data engineering. Based in Bellevue, WA, he blends research-grade rigor with production engineering pragmatism, often surfacing subtle backend improvements that yield outsized system gains.
9 years of coding experience
1 year of employment as a software developer
Master's degree, Cartography and Geographical Information System, Master's degree, Cartography and Geographical Information System at Beijing Normal UniversityBachelor's degree, Geographic Information System, Bachelor's degree, Geographic Information System at China University of Geosciences (Beijing)
Github Skills (30)
vector-search10
api-rest10
c-language10
restructuredtext10
postgresql10
restful-api10
compress10
approximate-nearest-neighbor-search10
rs10
simd10
compression10
rest-api10
cprogramming-language10
documentation10
kubernetes9
Programming languages (7)
Github contributions (5)
microsoft/pai
Apr 2020 - Apr 2022
Resource scheduling and cluster management for AI
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:2 releases, 274 reviews, 103 commits in 2 years
Contributions summary:Guoxin contributed significantly to the `microsoft/pai` repository, focusing on database migration, REST API updates, and enhancements to the Fluentd logging system. They implemented multithreading for Fluentd plugins and adjusted the schema for framework history. Further contributions included adding new API endpoints for job attempts and modifying configurations for the database. The user also worked on infrastructure changes, adding a node cordoning feature to the alert-manager.
cluster-managementmodel-trainingchainertensorflowcloud
microsoft/nni
May 2019 - Aug 2020
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Role in this project:Technical Writer & Documentation Specialist
Technical Writer & Documentation SpecialistContributions:2 releases, 6 reviews, 97 commits in 1 year 3 months
Contributions summary:Guoxin primarily contributed to the project by modifying documentation files, specifically within the `docs/en_US` directory. The commits involved fixing broken links, reorganizing content, and updating cross-file references to improve clarity and navigation. The changes included updating tutorials and detailed descriptions for the project's core features, such as tuners and accessors. The user also addressed formatting issues and ensured that the documentation was consistent with project updates.
pythonneural-architecture-searchengineeringtensorflowbayesian-optimization
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