Gage Dezoort
Postdoctoral Researcher at Princeton University
New Jersey, United States
Summary
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Senior🎓
Top SchoolGage Dezoort is a postdoctoral researcher at Princeton bridging physics and machine learning with a decade of research experience from undergraduate experiments to PhD-level theory in elementary particle physics. He focuses on principled approaches to neural network initialization and architecture selection and applies these tools to challenging physics problems within Princeton’s Physics and ORFE departments. His background spans experimental groups (UVA CMS and Mu2e) and theory-driven ML, giving him a rare perspective on both data-driven and first-principles methodologies. Based in New Jersey, he combines rigorous analytical training with hands-on model development and maintains a public research presence through his website and GitHub. Notably, his work emphasizes designing model inductive biases and initialization schemes that improve performance on physics tasks rather than ad hoc tuning.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Science (BS), Physics, Engineering Science, Bachelor of Science (BS), Physics, Engineering Science at University of VirginiaTuscaloosa AcademyDoctor of Philosophy - PhD, Elementary Particle Physics, Doctor of Philosophy - PhD, Elementary Particle Physics at Princeton University
Github Skills (26)
gnn-model10
geometric-deep-learning10
pytorch10
particle10
gnn10
graph10
tracking-algorithm10
deep-learning10
graph-neural-network10
graph-convolutional-networks10
clustering10
neural-network9
ai8
lpc7
ml5
Programming languages (3)
Github contributions (5)
GageDeZoort/azh_coffea
Oct 2022 - Mar 2025
Contributions:86 pushes, 1 branch in 2 years 5 months
GageDeZoort/gnns-for-tracking
Oct 2021 - Feb 2022
Contributions:19 commits, 15 pushes in 4 months
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