Jonathan Maack
Researcher IV - Computational Science
Englewood, Colorado, United States
Summary
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Top SchoolJonathan Maack is an applied and computational mathematician with eight years of experience translating deep theory into production-ready software for energy and defense applications. With a PhD in applied mathematics and a background in computational statistics, he builds high-performance stochastic and nonconvex optimization tools—often leveraging MPI, GPUs and emerging quantum techniques—for renewable energy grid operations and electromagnetic transient simulation. He pairs hands-on software engineering from a Lockheed Martin redesign of multi-threaded, service-oriented systems with academic experience developing JuMP/Julia packages and novel theories of geophysical turbulence. Skilled at breaking down complex interactions for clear documentation and collaboration, he also brings teaching experience that sharpens his communication of probabilistic modeling and uncertainty quantification. Outside work he pursues applied math curiosities like hockey analytics, reflecting a persistent drive to use math to reveal unexpected insights.
7 years of coding experience
11 years of employment as a software developer
Master of Science (MS) Computational and Applied Mathematics, Master of Science (MS) Computational and Applied Mathematics at Colorado School of MinesDoctor of Philosophy (PhD) Applied Mathematics, Doctor of Philosophy (PhD) Applied Mathematics at University of Massachusetts Amherst
Github Skills (60)
electricity10
slurm10
python10
energy10
linux10
configurations10
sympy9
multiple-versions9
hpc9
windows9
simulations9
stochastic9
mpi9
integer9
scientific-computing9
Programming languages (5)
Github contributions (5)
jmaack24/VortexSim
Jun 2018 - Nov 2024
Direct numerical simulator for 2D point vortices
Contributions:3 PRs, 19 pushes, 5 branches in 6 years 6 months
simulationsimulatorpointdirectquaternions
NREL/opf_matrices
Mar 2020 - Sep 2020
Contributions:19 commits, 2 pushes in 5 months
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