Research

Overview

My research has given me exposure to a variety of topics and methods across physics and astronomy.

Undergraduate Research

As an undergraduate at Johns Hopkins, I worked first in the experimental particle physics group of Petar Maksimovic. I used boosted decision trees and other machine learning techniques to help distinguish background and signal processes at the Large Hadron Collider (LHC).

I next worked in the group of Nadia Zakamska. We used time-series analysis techniques on a large dataset from the Wide-field Infrared Survey Explorer (WISE) to identify over 40,000 short-period (i.e. P < 1 day) binary stars. We also introduced new, less-computationally-intensive methods to identify periodic variables.

PhD Research

As a PhD student at the University of Michigan, my research has been in the field of particle phenomenology. My advisor is Aaron Pierce.

Projects:

• Dark Photon and Precision Electroweak Analysis: Explored the impact that an electroweak-scale dark photon would have on the precision electroweak fit.

• Dark Sink Dark Matter: Studied a modification to the typical freeze-in paradigm that allows for larger couplings to the Standard Model. I contributed to the public code that accompanied this paper.

• WIMP Parameter Space: Studied a paradigmatic model of a Weakly Interacting Massive Particle (WIMP) and charted out the remaining parameter space.

• Current Work: Recently, I have been thinking a lot about early universe scenarios where the dark sector and standard model decouple in new and interesting ways.

Publications

For more details, see here for a list of my publications.

Technical Skills

Python, C++, SQL, Mathematica, Jupyter, Microsoft 365, Bash, Zsh, Git, LaTeX, Data Analysis, Statistics, Optimization, Linear Algebra, Machine Learning (TensorFlow), Quantum Computing, Quantum Information