Seth Goodman is a Research Scientist and Data Engineer with 11 years of experience, currently building scalable ML pipelines and infrastructure at AidData to turn satellite imagery and geospatial data into development metrics. He designs and operationalizes distributed data systems managing over 50TB used by thousands of researchers, and pairs this production focus with academic dissemination through papers, workshops, and funding proposals. Trained as a PhD in Computational Geography with prior MS and BS degrees in engineering, Seth blends rigorous spatial analytics with practical software engineering. He contributes to open-source geospatial tooling—improving test coverage and robustness in projects like python-rasterstats—highlighting a detail-oriented approach to reproducible research.
11 years of coding experience
Master of Science (M.S.), Electrical Engineering, Master of Science (M.S.), Electrical Engineering at Villanova University
Doctor of Philosophy - PhD, Computational Geography, Doctor of Philosophy - PhD, Computational Geography at William & Mary
Summary statistics of geospatial raster datasets based on vector geometries.
Role in this project:
QA Engineer / Test Automation Engineer
Contributions:14 commits, 11 PRs, 41 comments in 1 year 10 months
Contributions summary:Seth focused on enhancing the test coverage for the `python-rasterstats` repository. Their commits added new test cases, specifically targeting functionality related to argument aliases, handling of `NaN` values, and the correct output of feature properties. They also fixed existing test cases and addressed import issues, demonstrating a focus on improving the reliability and completeness of the testing suite.
Repository for AidData's Geospatial Global Chinese Development Finance Dataset (GeoGCDF)
Contributions:4 releases, 145 commits, 5 PRs in 1 year 3 months
geodatachinesegeospatialgeographydataset
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