Steven Farrell
Machine Learning Engineer at Berkeley Lab
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolSteven Farrell is a Machine Learning Engineer at Lawrence Berkeley National Laboratory with 14 years of experience bridging high-energy physics research and applied ML on HPC systems. Trained as a physicist with a PhD from UC Irvine and a long track record on the ATLAS experiment at CERN, he builds ML infrastructure for scientific teams and optimizes distributed training for thousands of users at NERSC. He combines deep domain expertise in particle physics—having contributed to top quark and supersymmetry analyses—with practical skills in software, simulation, and vendor collaboration to deploy performant ML stacks on supercomputers. Known for translating complex research workflows into reproducible, high-performance pipelines, he also leads community training and documentation to help researchers exploit HPC for ML.
13 years of coding experience
6 years of employment as a software developer
Bachelor of Science (B.S.), Physics and Mathematics, Bachelor of Science (B.S.), Physics and Mathematics at University of Minnesota-DuluthDoctor of Philosophy (Ph.D.), Physics, Doctor of Philosophy (Ph.D.), Physics at University of California, Irvine
English, French
Github Skills (84)
benchmark10
python10
deep-learning10
gpu10
ml10
neural-network10
data-science10
policies10
tensorflow10
baidu10
keras-tensorflow10
machine-learning10
keras10
deep-neural-networks10
numpy9
Programming languages (8)
Github contributions (5)
susynt/SusyCommon
Jun 2012 - May 2014
Contributions:562 commits, 3 comments in 1 year 11 months
cernsvn
NERSC/nersc-tf-tests
Jun 2021 - Mar 2024
Contributions:2 reviews, 8 PRs, 12 pushes in 2 years 9 months
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