I work on large-scale geospatial analysis at NCEAS, where I help build the Wildfire Resilience Index. Most days I’m wrangling rasters and time series data in R and Python, turning raw indicators like NDVI, precipitation, land cover, and tree traits into clear, reusable layers and maps. I care a lot about reproducibility and making results easy for others to use so things like consistent CRS/resolution, sensible nodata handling, and little utilities that save teammates time.
Before this, I finished an M.S. in Environmental Data Science at the UCSB Bren School. I’ve also led and contributed to research on how dietary shifts and marine aquaculture affect environmental pressures.
Tools I reach for: R/terra/sf, GDAL, Python/rasterio/pandas, Quarto, Git/GitHub.
Find me: LinkedIn
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Wildfire Resilience Index (WRI) — Automated geospatial pipeline and reporting across indicators → domain scores.
Link: https://www.wildfireindex.org/ -
Renewable Energy Siting (Capstone) — Stats + ML to map likely utility-scale wind/solar siting; includes an interactive summary.
Dashboard: https://energysiting.github.io/energysiting-dashboard/#overview -
Dietary Shifts & Environmental Pressure — First-author paper exploring how global diet changes redistribute environmental impacts across countries.
Link: The distribution of environmental pressures from global dietary shiftData and Code: https://zenodo.org/records/13001955
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Marine Aquaculture Analysis — Lead analyst on work assessing where current policy performs well and where it may need to adapt.
Link: Winners and losers in U.S. marine aquaculture under climate changeRepo: https://github.com/catfong/ERL_US_marine_aquaculture_potential