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mikemahoney218

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R, Python, and using data to understand this complex world we live in

Funding Links: https://github.com/sponsors/mikemahoney218

GitHub Sponsors Profile

Mike Mahoney, Now in TreeD
I'm a PhD candidate in Colin Beier's lab at SUNY-ESF, working on machine learning for ecological outcomes, model interpretability, and landscape visualization. I also maintain a handful of R packages:

Package
What it does

spatialsample
A tidymodels package for spatial resampling

waywiser
Yardstick extensions for measuring spatial structure in model residuals

terrainr
Transform geospatial data for rendering in Unity 3D (and download data from the USGS National Map)

unifir
A unifying interface for calling Unity from R

heddlr
Functionally compose R Markdown from repeated components

proceduralnames
Generate human-readable random identifiers

plantr
Download data from the USDA PLANTS API

mvdf
A standardized approach to using R as a frontend for the Blender 3D rendering program

I'm also a contributor to plenty of other libraries across the R ecosystem, focusing on tools for spatial analytics and modeling.

Featured Works

mikemahoney218/quarto-arxiv

Quarto template for arXiv preprints

Language: TeX - Stars: 92
ropensci/unifir

A unifying interface for calling Unity from R

Language: R - Stars: 29
ropensci/terrainr

Get DEMs and orthoimagery from the USGS National Map, georeference your images and merge rasters, and visualize with Unity 3D

Language: R - Stars: 72
tidymodels/spatialsample

Create and summarize spatial resampling objects 🗺

Language: R - Stars: 73
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