Jason St. John

Statistics

Publications

Citations

155

H-Index

Active since

2020

Affiliations

Fermi National Accelerator Laboratory(Current)

Thomas Jefferson National Accelerator Facility

Columbia University

Argonne National Laboratory

Brookhaven National Laboratory

Jason St. John is an author at Fermi National Accelerator Laboratory specializing in linear optimization, hardware optimization, and bayesian optimization.

ORCID

Top concepts

EngineeringBayesian MethodsComputer ScienceMachine LearningLinear ProgrammingAccelerator PhysicsSystems EngineeringBayesian OptimizationComputational ScienceHardware Optimization

Publications per year

2020–2024

Publications

Bayesian optimization algorithms for accelerator physics

Ryan Roussel, Auralee Edelen, Tobias Boltz et al. · Physical Review Accelerators and Beams · 2024 · 50 citations · Full text

Large-scale Global Optimization, Engineering, Machine Learning +18

Anvil - System Architecture and Experiences from Deployment and Early User Operations

X. Carol Song, Preston Smith, Rajesh Kalyanam et al. · Practice and Experience in Advanced Research Computing · 2022 · 44 citations · Full text

Real-time Artificial Intelligence for Accelerator Control: A Study at\n the Fermilab Booster

Jason St. John, Diana Kafkes, Jovan Mitrevski et al. · arXiv (Cornell University) · 2020 · 38 citations · Full text

Measurement of nuclear effects in neutrino-argon interactions using generalized kinematic imbalance variables with the MicroBooNE detector

P. Abratenko, O. Alterkait, D. Andrade Aldana et al. · Physical review. D/Physical review. D. · 2024 · 13 citations · Full text

Uncertainty aware machine-learning-based surrogate models for particle accelerators: Study at the Fermilab Booster Accelerator Complex

Malachi Schram, Kishansingh Rajput, Karthik Somayaji NS et al. · Physical Review Accelerators and Beams · 2023 · 10 citations · Full text

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