Christine Sweeney
Scientist at Supercomputing 2015-17 Conferences
Los Alamos, New Mexico, United States
Summary
👤
Senior🎓
Top SchoolChristine Sweeney is a scientist and software engineer with 14+ years at Los Alamos National Laboratory applying AI and data-intensive methods to scientific problems, from exascale beamline analysis to AI/ML workflow data management. She combines deep systems experience—programming languages, compilers, Legion task-based runtimes, GPU acceleration, and reconfigurable computing—with hands-on scientific applications like ptychography, reinforcement learning for science, and quantum key distribution. Her work bridges research and production: building domain-specific compilers and runtime libraries as well as in situ visualization and data infrastructure for simulation and experiments. Based in Los Alamos, she brings a rare blend of low-level systems craftsmanship and domain science fluency, and often operates at the intersection of HPC, AI, and experimental workflows.
14 years of coding experience
18 years of employment as a software developer
Master of Science (M.S.), Computer Science, Master of Science (M.S.), Computer Science at University of WashingtonNon-degree, Re-entry Program in Computer Science, Non-degree, Re-entry Program in Computer Science at University of California, BerkeleyNon-degree, Math and Science, Non-degree, Math and Science at University of New MexicoElectrical and Computer Engineering, Electrical and Computer Engineering at The University of New Mexico
Github Skills (11)
simulation9
lammps8
perf5
q-learning5
deep-reinforcement-learning4
reinforcement-learning4
scalable4
performance-counters3
program-analysis2
viewer2
bandit1
Programming languages (3)
Github contributions (5)
cmahrens/cinema_bandit
Apr 2020 - Apr 2020
Cinema:Bandit experimental viewer
Contributions:1 push in 1 day
viewerbanditcinema
lanl/scout
Jan 2012 - Sep 2015
Contributions:112 commits in 3 years 9 months
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