Grant Buster
Data Scientist
Boulder, Colorado, United States
Summary
👤
Senior🎓
Top SchoolGrant Buster is a data scientist in Boulder with 11 years of experience applying engineering rigor to clean energy and resilience challenges. At the National Laboratory of the Rockies he has led development of cornerstone tools like the NSRDB, reV, and sup3r, combining climate science, energy-systems modeling, and generative ML to improve renewable integration and extreme-weather planning. Earlier work at NuScale honed his simulation-based risk analysis and automation skills, producing production-ready Python and MATLAB tools used in a U.S. SMR design certification effort. He holds an M.S. from UC Berkeley where he built and automated x‑ray tomography experiments and software—an unusual experimental-to-software background for an energy modeler. Colleagues rely on him to bridge deep technical implementation with policy-relevant energy planning.
11 years of coding experience
7 years of employment as a software developer
Master's Degree Nuclear Engineering, Master's Degree Nuclear Engineering at University of California, Berkeley
English
Stackoverflow
41reputation
483reached
2answers
0questions
Github Skills (55)
energy-data10
abstract-syntax-tree10
sarif10
machine-learning10
energy10
extraction10
geospatial10
perl10
generative-adversarial-network10
super-resolution10
renewable-energy10
climate-change10
deep-learning10
tensorflow10
source-code-analysis10
Programming languages (5)
Github contributions (5)
NatLabRockies/osos
Sep 2021 - Dec 2022
Open Source Ops and Statistics (OSOS)
Contributions:139 commits, 2 PRs, 25 pushes in 1 year 3 months
statistics
NatLabRockies/phygnn
Jul 2020 - Oct 2022
physics-guided neural networks (phygnn)
Contributions:48 reviews, 196 commits, 55 PRs in 2 years 3 months
neural-networkmachine-learningneural-networksdeep-learning
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