Experience
I work full time as a software engineer primarily working on machine learning and data analytics
software using tools like PyTorch, PySpark & Azure/AWS Databricks.
Outside of my full time job I conduct research as
an independent research
scientist.
I have previously collaborated with the Quantum Fields and Quantum Information
group lead by Olivier Pfister at the University of Virginia where I worked on machine learning applications for
photonic quantum computing. I have also collaborated with the Quantum Physical Learning Group,
which is a collaboration lead by J. M. Schwarz at Syracuse University and Olivier Pfister at the University of Virginia,
that explores how to perform analog machine learning in quantum systems.
My research is largely interdisciplinary, specifically at the
intersection of quantum computing/information and AI/ML.
I am also interested in the broader intersection of physics and computing.
I also contribute to
open source scientific software
such as
QuTiP as well as open source teaching resources for data science/ML such as the following on
Bayesian statistics.
Education
I hold a M.S. in computer science with a concentration in machine learning
from the Georgia Institute of Technology.
I hold a B.S. in computer science and
physics with a minor in mathematics from the University of Virginia. While there I completed my
distinguished major thesis
on quantum computing applied to machine learning problems with graphs which was
supervised by
Olivier Pfister.
Honors
• University of Virginia Echols Scholar
• University of Virginia Computer Science B.A. - Highest distinction
• University of Virginia Physics B.S. - Distinction
