Andrew Reisner
Staff Scientist at Los Alamos National Laboratory
Frederick, Maryland, United States
Summary
👤
Senior🎓
Top SchoolAndrew 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.
12 years of coding experience
University of Illinois Urbana-ChampaignWartburg College
Github Skills (53)
sparse10
parallel10
mpi10
solver10
overlay10
caliper9
large-scale9
python9
linux9
topology9
parallel-computing9
perf9
scale9
configurations9
scientific-computing9
Programming languages (5)
Github contributions (5)
SIAM-at-Illinois/Getting-Started-Series
Jan 2014 - Apr 2017
Contributions:21 commits in 3 years 3 months
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
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