About

I am an undergraduate at The Massachusetts Institute of Technology (Class of 2025), majoring in Physics and Mathematics. My academic interests broadly encompass better understanding foundational physics through combining advances in theoretical physics and machine learning.

I was born in Charlotte, North Carolina, and attended local schools until high school when I was accepted to the North Carolina School of Science and Mathematics (NCSSM). At NCSSM, I continued to study mathematics and physics. I was accepted to MIT to study physics but chose to delay my admission by one year due to COVID-19. During my gap year, I self-studied several MIT courses and volunteered within my community working as a data analyst for non-profits and teaching at a local elementary school. 

Currently, I am developing non-Euclidean machine learning techniques for physics analysis, working as an undergraduate researcher in MIT's Fast Machine Learning Lab. Additionally, I hold a junior researcher position at The NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI). My research journey has been diverse, involving projects in gravitational lensing, digital signal processing and passive coherent location, and astroparticle physics.