About Me

I'm a Physics Ph.D. student at the University of Virginia, specializing in theoretical and experimental nuclear physics. My research focuses on the spin distribution of hadrons through the study of the Sivers Distribution of polarized proton targets.

I apply machine learning and AI techniques to both experimental instrumentation and theoretical prediction analysis, working under the advisorship of Professor Dustin Keller.

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Research Focus

Nuclear Spin Physics

Investigating the Sivers Distribution in polarized proton targets to understand fundamental spin properties of hadrons.

ML Applications

Developing machine learning models for experimental data analysis and theoretical predictions in nuclear physics.

Experimental Design

Creating innovative instrumentation approaches for nuclear physics experiments using modern computational methods.

Projects

ML for Particle Identification

Developing deep learning models to improve particle identification in detector data.

TensorFlow Python Nuclear Physics

Sivers Function Analysis

Statistical analysis of experimental data to extract the Sivers function parameters.

Data Analysis Statistics ROOT

Detector Simulation

Monte Carlo simulations of particle interactions in detector systems.

GEANT4 C++ Simulation