Gregory Matousek
Machine Learning Engineer at CoVar
Durham, North Carolina, United States
Summary
👤
Senior🎓
Top SchoolGregory Matousek is a machine learning engineer and nuclear physics PhD candidate with nine years of experience building analysis pipelines and AI models for high-energy nuclear experiments. He combines C++ and Python engineering with TensorFlow and PyTorch research to deploy detector-clustering and photon-classification models that improve experimental efficiency and physics reach. At Duke he authored peer-reviewed work and maintains public repositories for detector clustering and spin-physics simulations, applying Monte Carlo methods to extract high-precision dihadron asymmetries. Now transitioning into industry at CoVar, he brings a rare blend of hands-on experimental analysis, production ML, and mentorship for reproducible scientific software. A less obvious strength is his track record of translating detector-level innovations into measurable improvements in physics results, not just model metrics.
9 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD Nuclear Physics, Doctor of Philosophy - PhD Nuclear Physics at Duke UniversityPhysics Nuclear Physics, Physics Nuclear Physics at Stony Brook University
Github Skills (8)
simulation10
hosting10
python9
dis9
raycasting2
spin1
diffraction1
bidirectional1
Programming languages (3)
Github contributions (5)
Gregtom3/CLAS12Analysis
May 2022 - Nov 2022
Software for analyzing Dihadrons from CLAS12 SIDIS
Contributions:2 PRs, 136 pushes, 6 branches in 6 months
analyzingpython
Gregtom3/clas12_tutorial
May 2023 - Mar 2025
Contributions:27 pushes, 1 branch in 1 year 10 months
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