Xiaodong Jiang
Staff Research Data Scientist
Menlo Park, California, United States
Summary
🤩
Rockstar🎓
Top SchoolXiaodong Jiang is a Staff Research Data Scientist at Meta with 11 years of experience building infrastructure for generic time series analysis, including forecasting, detection, and feature embedding. He holds a Ph.D. in Statistics and an MS in Computer Science, blending rigorous academic training with production-focused engineering. At Meta he leads a cross-functional team and helped open source Kats, a widely used toolkit for time series analysis, contributing to its readiness and maintainability. His background spans graph ML and deep learning, and he brings a practical attention to code quality—evidenced by efforts to standardize licensing and automate repository maintenance—alongside deep statistical expertise.
11 years of coding experience
3 years of employment as a software developer
University of GeorgiaBachelor's degree, Mathematics, Bachelor's degree, Mathematics at Beijing University of Technology
English, Chinese
Github Skills (9)
code-standards10
standardized10
python10
standardization10
rights-management9
bash9
licensing9
key-management9
open-source9
Programming languages (2)
Github contributions (5)
facebookresearch/Kats
Mar 2021 - Aug 2022
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:74 commits, 2 PRs, 2 pushes in 1 year 4 months
Contributions summary:Xiaodong primarily contributed to the codebase by adding copyright headers to existing Python files. This standardization effort included modifying multiple files, ensuring the inclusion of the necessary copyright and licensing information. The changes also involved the creation and utilization of a bash script to automate the process across all Python files within the repository. This indicates a focus on code maintainability and open-source readiness.
forecastingstatisticspythontime-series-analysisunderstanding
iamxiaodong/battelship
Mar 2015 - Apr 2016
Contributions:1 push in 1 year 1 month
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