Qingyuan Zhao - Data Engineer

Qingyuan Zhao

Data Engineer

Shenzhen, Guangdong Province, China

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Summary

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Senior

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Top School

Qingyuan Zhao is a data engineer with 11 years' experience based in Shenzhen, currently delivering production data solutions at Pingan Tech. Trained in civil and transportation engineering at Tsinghua and Cornell (M.S., 3.97/4.30), he blends strong quantitative modeling skills with practical data engineering. He has contributed to open-source statistical tooling—implementing the mr.raps Mendelian Randomization method in the widely used TwoSampleMR R package—demonstrating comfort shipping statistical algorithms into shared libraries. Known as reliable and responsible, he focuses on robust back-end implementations and data-driven analysis. Qingyuan’s background in transportation statistics and economics gives him a cross-disciplinary perspective that helps translate complex models into scalable engineering solutions.

10 years of coding experience

Master of Science (M.S.), Transportation Engineering, 3.97/4.30, Master of Science (M.S.), Transportation Engineering, 3.97/4.30 at Cornell University Graduate School

Bachelor's degree, Civil Engineering, 90/100, Bachelor's degree, Civil Engineering, 90/100 at Tsinghua

Bachelor’s Degree, Economics (Second Degree), Bachelor’s Degree, Economics (Second Degree) at 清华大学经济管理学院 Tsinghua University School of Economics and Management

English, Chinese

Github Skills (3)

r10

statistics10

develop9

Programming languages (3)

RC++HTML

Github contributions (5)

MRCIEU/TwoSampleMR

Jan 2018 - Jan 2021

R package for performing 2-sample MR using MR-Base database

Role in this project:

Back-end Developer & Data Scientist

Contributions:9 commits, 1 PR, 2 comments in 3 years

Contributions summary:Qingyuan implemented a new Mendelian Randomization (MR) method, "mr.raps," within the R package. They modified existing functions related to MR analysis, including parameter adjustments and incorporation of the new method into the core `mr` function. The user also made improvements to the `steiger_filtering` function. These changes indicate a focus on extending the package's functionality and enhancing its statistical methods.

r-packagedatabaserstats

qingyuanzhao/Causal-Inference-Lectures

Feb 2021 - May 2022

Contributions:6 commits, 2 pushes in 1 year 2 months

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