Research Overview

I have conducted within and across the fields of mathematics, quantum and fluid physics, computational and materials chemistry, molecular biology, and applied computer science. I am broadly interested in multiscale modeling of physical, chemical, and biological systems, with an emphasis on integrating computational frameworks and theoretical descriptions with experiment. My current materials modeling research within the Kozinsky Lab at Harvard centers on machine-learned exchange-correlation functionals for Density Functional Theory (DFT) methodologies, method development for top-down differentiable learning of neural -network (NN) potentials, and asymmetric construction of NN potentials.