Published work and technical foundations
My research background is in neutrino physics, detector analysis, simulation, and machine learning. This page is intentionally limited to mature, published, or already public work.
I earned my PhD in physics at the University of Tennessee, working on the PROSPECT neutrino experiment at Oak Ridge. The work combined detector physics, statistical analysis, particle transport simulation, and machine learning for event reconstruction and background reduction.
That background trained me to build software and analysis pipelines where correctness, noise tolerance, and system-level reasoning are non-negotiable. The same mindset now carries over into consulting and technical product work.
Signal Processing
Analysis of detector signals under noisy experimental conditions, with emphasis on extracting reliable measurements from imperfect data.
Machine Learning
Applied ML methods for event reconstruction and classification, improving usable detector statistics in the PROSPECT experiment.
Simulation
Experience with particle transport simulation and scientific software in experimental physics contexts.
Research Software
Building analysis tooling, data workflows, and reproducible technical systems around demanding scientific questions.
What is public stays public
Ongoing research and unreleased technical projects are not described here until they are ready. This page is meant to establish background, not tease incomplete work.
If you are exploring a scientific or technically demanding problem and want to discuss collaboration, reach out directly.