Josue Rodriguez
Senior Data Scientist
Davis, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJosue Rodriguez is a Senior Data Scientist with a PhD in Quantitative Psychology and nine years of experience applying statistics, Bayesian methods, and machine learning to product and research problems. He builds personalized learning systems at McGraw Hill and has a track record of coordinating large-scale projects, authoring academic publications, and teaching graduate students advanced analytics. His work on AI Fairness 360’s R interface highlights a practical commitment to responsible ML and bias mitigation in real-world tooling. Comfortable translating technical complexity for non-technical stakeholders, he blends behavioral insight with production-ready modeling to drive measurable outcomes. Colleagues benefit from his unusual mix of psychometrics expertise, hands-on ML engineering, and product-focused collaboration.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Psychometrics and Quantitative Psychology, Doctor of Philosophy - PhD Psychometrics and Quantitative Psychology at University of California, DavisM.A. Experimental Psychology, M.A. Experimental Psychology at Cal Poly Humboldt
Spanish, French
Github Skills (9)
machine-learning10
f10
tensorflow10
n10
ai10
r10
protobuffer9
protobuf9
python4
Programming languages (3)
Github contributions (5)
Trusted-AI/AIF360
Jun 2022 - Jun 2022
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 7 commits, 3 PRs in 6 days
Contributions summary:Josue primarily focused on modifying and maintaining the `aif360-r` component, which appears to be an R interface for the AIF360 library. They updated package versions for dependencies like TensorFlow and Protobuf within the R environment setup. The user also worked on a function related to adversarial debiasing, passing arguments and refining documentation.
fairness-mlpythondiscriminationbias-reductionfairness-testing
josue-rodriguez/bayeslincom
Jul 2020 - Sep 2021
Contributions:70 commits, 6 PRs, 52 pushes in 1 year 2 months
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