Current Position: Senior Software Engineer - Scientific Machine Learning
Current Institution: NVIDIA
Degree Year: 2017
Advisor: Bonnie Fleming
Degree Year: 2017
Dissertation Title: First Detection of Low Energy Electron Neutrinos in Liquid Argon Time Projection Chambers
Dissertation Abstract: Electron neutrino appearance is the signature channel to address the most pressing questions in neutrino oscillations physics, at both long and short baselines. This includes the search for CP violation in the neutrino sector, which the U.S. flagship neutrino experiment DUNE will address. In addition, the Short Baseline Neutrino Program at Fermilab (MicroBooNE, SBND, ICARUS-T600) searches for new physics, such as sterile neutrinos, through electron neutrino appearance. Liquid argon time projection chambers are the fore-front of neutrino detection technology, and the detector of choice for both short and long baseline neutrino oscillation experiments.
This work presents the first experimental observation and study of electron neutrinos in the 1-10 GeV range, the essential oscillation energy regime for the above experiments. The systematic uncertainties for an electron neutrino appearance search for the Fermilab Short Baseline Neutrino Program are carefully quantified, and the characterization of separation between electrons and high energy photons is examined.
Information updated 03/10/2026