Xiao Meng
Senior AI ML Data Scientist
Austin, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolXiao Meng is a Senior AI/ML Data Scientist based in Austin with 15 years of experience blending rigorous academic research and production machine learning at companies like General Motors and in academia. He holds a PhD in Agricultural Economics and translated advanced econometric methods (BLP, Vuong tests, likelihood-ratio algorithms) into practical analyses and teaching while earning awards for pedagogy and service. At GM he focuses on vehicle-dynamics forecasting and ETA modeling, applying production-grade ML and data visualization techniques from his Texas McCombs bootcamp training. Xiao also contributes to open-source tooling—improving httpstat for clearer HTTP/HTTPS diagnostics and JSON metrics—demonstrating a pragmatic back-end skills set alongside his statistical depth. Known for turning theoretical models into deployable solutions, he brings a rare combination of econometric rigor, hands-on engineering, and clear communication to cross-functional teams.
14 years of coding experience
7 years of employment as a software developer
Certificate, Data Analysis and Visualization Boot Camp at Texas McCombs, Certificate, Data Analysis and Visualization Boot Camp at Texas McCombs at The University of Texas at AustinDoctor of Philosophy - PhD, Agricultural Economics, Doctor of Philosophy - PhD, Agricultural Economics at Penn State University
Github Skills (10)
json10
http10
curl10
python10
cli10
visualizations9
subprocess9
visualization9
error-handling8
testing7
Programming languages (21)
Github contributions (5)
reorx/httpstat
Aug 2016 - Oct 2022
curl statistics made simple
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 releases, 2 reviews, 93 commits in 6 years 2 months
Contributions summary:Xiao primarily contributed to the development of the `httpstat` tool, focusing on enhancing its functionality and improving its usability. Their work included refactoring the code to divide the template for HTTP and HTTPS requests, adding features to display headers, body, and download/upload speed. The user also implemented error handling, added support for Python 3, and improved the display of output, including the ability to show metrics in JSON format.
clistatisticspythoncurlvisualization
reorx/learn_spider
Jan 2016 - Apr 2017
Contributions:7 commits, 5 pushes, 1 branch in 1 year 3 months
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