• Led the development of an AI-powered saliva test for early detection of neurodegenerative diseases, revolutionizing diagnostics.• Applied machine learning and AI expertise to drive innovation in neurodegenerative disease diagnostics.• Spearheaded the mission at CogniSci Labs to improve patient outcomes and quality of life through early and accurate detection.

My research focused on the development, implementation, and application of new theoretical methods in quantum chemistry. Specifically, my work focused on the development of (1) machine learning models and (2) quantum embedding theory. In my machine learning work, we described the potential energy surfaces of atoms by utilizing neural networks and are specifically exploring transfer learning and transferability. In quantum embedding the framework allows systems to be divided into smaller subsystems that can be treated at different levels of theory, with the intersubsystem potential calculated using embedded density functional theory. I have applied this methodology to large condense phase systems, including homogenous catalysts and enzymes. My research has been published in top chemistry journals, such as Nature Chemistry, Proceedings of the National Academy of Sciences, and the Journal of the American Chemical Society. I received the NSF CAREER award in 2020 and the 2020 Machine Learning in the Chemical Sciences and Engineering Award given by the Camille and Henry Dreyfus Foundation.

Research Project: The fundamental quantum chemical modeling of CO2 reductionAdvisors: Martin Head-Gordon and Alexis BellThis project aims to contribute mechanistic insight from electronic structure computations on experimentally relevant systems, as well as attempting to give insights that can impact the designprinciples for future catalysts. In support of this main objective, the project includes the development of new computational methods used for the modeling.

Dissertation Topic: "Density functional theory embedding for correlated wavefunctions"Advisor: Thomas F. Miller, IIIMy dissertation focused on the development and application of embedded density functional theory and embedded wave function theory methods. This methodology was applied to large condense phase systems, including homogenous catalysts and enzymes. This work lead to a series of publications, listed below.