Yijin Wang
Incoming Intern at Columbia University
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolYijin Wang is a PhD candidate in Biostatistics at Columbia University with nine years of experience applying statistical machine learning to public health problems. She helped lead development of ensemble and Gaussian process models at the Reich Lab’s CDC-funded COVID-19 Forecast Hub, authored R packages (covidHubUtils, covidData) and automated validation workflows for forecasts from 90+ teams. As a long-running TA across data science, probability, and pharmaceutical statistics courses, she pairs rigorous research with clear communication to public health stakeholders. Incoming intern at Genentech, she brings practical software engineering skills (TensorFlow, TensorFlow Probability, R, GitHub Actions) alongside academic depth. Notably, she combines hands-on model engineering with reproducible tooling that enabled operational forecasting during the pandemic.
8 years of coding experience
5 years of employment as a software developer
Bachelor of Arts - BA, Computer Science, Statistics, Bachelor of Arts - BA, Computer Science, Statistics at Mount Holyoke CollegeDoctor of Philosophy - PhD, Biostatistics, Doctor of Philosophy - PhD, Biostatistics at Columbia UniversityComputer Science, Computer Science at Aquincum Institute of Technology (AIT-Budapest)iOS Development, iOS Development at CodePath
English, Chinese
Github Skills (22)
atmospheric-modelling10
visualization10
standardized10
bootstrapping10
analytics10
forecasts10
github-pages10
forecast10
data-access10
bayesian7
modeling6
bayesian-inference5
quantile5
machine-learning5
python3
Programming languages (4)
Github contributions (5)
dsheldon/mechbayes
Sep 2021 - Jan 2022
Bayesian modeling of COVID-19, sometimes mechanistic
Contributions:55 commits, 1 PR, 32 pushes in 4 months
modelingbayesian-inferencebayesianmachine-learning
reichlab/covid19-forecast-hub-validations
Jun 2021 - Jul 2022
Contributions:19 reviews, 45 PRs, 79 pushes in 1 year
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