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Rich Pauloo, PhD

Data Scientist

Hi ๐Ÿ‘‹, my name is Rich.

I spend most of my days writing code (mostly R, Python, SQL) to clean, visualize, and model data. I have a PhD in computational hydrogeology, where I simulated and visualized 3D contaminant transport in aquifers.

I love to surf ๐Ÿ„โ€, climb mountains ๐Ÿง—๐Ÿผ, tinker on bikes ๐Ÿšดโ€, read and learn new things ๐Ÿ“š, play guitar ๐ŸŽธ, and cook ๐Ÿง‘โ€๐Ÿณ.

Interests

  • ๐Ÿ‘จโ€๐Ÿ’ป data science
  • โ›ฐ๏ธ expedition behavior
  • ๐Ÿงฎ mathematical modeling
  • ๐Ÿ“ก sensor networks

Education

  • PhD in Computational Hydrogeology, 2020

    University of California Davis

  • BA in Integrative Biology, minor in Conflict Resolution, 2011

    University of California Berkeley

Projects

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r4wrds

R for water Resources Data Science.

gsp dry wells .com

Domestic well failure prediction and cost estimates in critically overdrafted basins.

low cost sensor networks

Real-time sensor networks and dashboards for monitoring environmental data.

cal water quality .com

Automated water quality reports for > 3,000 California public water systems. ๐Ÿ† Winner 2019 California Water Data Challenge.

interpretable random forests

Cumulative variable importance.

textme

Text yourself from R when long running jobs complete.

Tulare basin TDS

Groundwater quality data visualization.

CA well report filter

Upload a shapefile of a study area to return clean OSWCR data from that area.

CA well reports

Exploratory data analysis of California's Online State Well Completion Report Database.

Fatal landslide prediction

Using random forests, boosting, LDA, and QDA with variable probability thresholds for global landslide classification.

AbstR

An adaptation of PapR to 30,000 American Geophysical Union abstracts.

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