I am a physics PhD student at the Massachusetts Institute of Technology (MIT). My background is in physics, mathematics, data science, and applied sciences in engineering.
Quantum Field Theory
Jets and QCD
Beyond the Standard Model
I am primarily interested in the intersection between theoretical particle physics and modern machine learning methods. How can we use machine learning to understand particle physics, and how can we use particle physics to understand machine learning?
We present a machine learning framework for performing maximum likelihood inference with Guassian uncertainty estimation, which also quantifies the mutual informaiton between the unobservable and measured quantities.
We search for evidence of Vector-Like Quark (VLQ) production in the CMS Detector of the Large Hadron Collider's entire second run, and set (as of publication) the highest mass limits on VLQ hadronic decays