🏆When I started at UTK I was the recipient of the Tennessee Graduate Fellowship for Research Excellence. I was awarded this fellowship for my work with the ALICE experiment in my undergraduate studies. The accompanying $40,000 partially supported my work as a graduate research assistant in my first four years of study.
🧪 My research investigates the process of hadronization, or the combination of free quarks and gluons into hadrons, like protons and pions. In the process I have developed a novel sampling bias technique to better model gaussian mixtures and determine the fractions of different particle species. This work could help rule out incorrect theories of hadronization, and potentially shed light on how the presence of a quark-gluon plasma can modify hadronization.
🤖 I published two papers in Physical Review C, a first- and a second-author paper, both exploring interpretable and explainable machine learning techniques applied to physics problems. In both papers, we use knowledge distillation on complex models to train simpler or more informative models. The first paper uses a simple decision rule to distill a random forest trained to classify background objects. We achieved over 95% of the background rejection with a simple rule.
📖First Author Paper In our second paper, we used symbolic regression to distill a neural network trained to estimate the background contamination in a particular quantity. The resulting formula was easily justified by previous work and demonstrated a blind spot in current experimental standards.
📖Second Author Paper