Andrew Reisner

Staff Scientist at Los Alamos National Laboratory

Frederick, Maryland, United States
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Summary

👤
Senior
🎓
Top School
Andrew Reisner is a Staff Scientist at Los Alamos National Laboratory with a PhD in Computer Science from UIUC and 12 years of experience applying data mining, pattern recognition, and clustering techniques to large-scale, high-performance computing problems. He combines rigorous academic training with hands-on research and engineering to model and analyze complex datasets for scientific and defense applications. Based in Frederick, Maryland, he has a track record of moving algorithms from prototype to production-scale environments and thrives on optimizing computational workflows for speed and scalability. Colleagues describe him as comfortable at the intersection of theory and systems engineering, able to translate mathematical insights into efficient, parallelizable code. An understated strength is his fluency in bridging multidisciplinary teams—bringing domain scientists and HPC practitioners together to solve hard, data-driven questions.
code12 years of coding experience
bookUniversity of Illinois Urbana-Champaign
bookWartburg College
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Github Skills (42)

sparse10
parallel10
solver10
mpi10
overlay10
type-safety10
large-scale10
scale10
parallel-computing10
cpp10
caliper9
linux9
windows9
macos8
scientific-computing8

Programming languages (5)

C++ShellCFortranPython

Github contributions (5)

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cedar-framework/cedar

Aug 2015 - Apr 2020

A robust, variational multigrid library implementing BoxMG on large scale parallel systems.
Contributions:574 commits, 3 PRs, 108 pushes in 4 years 9 months
multigridparallelscalelarge-scalevariational
Contributions:21 commits in 3 years 3 months
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