Conducting theoretical physics research regarding the application of feedforward neural networks to the Variational Monte Carlo method, for use in more efficiently approximating the ground state energy of many-particle systems. Research conducted under the guidance of Prof. Paulo Bedaque.

Continued previous research, this time focusing on the generation of quantum circuits for the Horn model. Devised and implemented methods of obtaining quantum circuits for arbitrary large unitary matrices in Python. Research was conducted under the guidance of Prof. Paulo Bedaque and Prof. Andrei Alexandru.

Conducted theoretical physics research with the NuQS collaboration on generating quantum circuits for group operations of subgroups of S(1080), for use in simulation of Lattice QCD gauge theories on quantum computers. Also investigated automated quantum circuit synthesis methods, and wrote a small order quantum circuit solver using SAT/SMT methods in Python. Research was conducted under the guidance of Scott Lawrence.