Professor Kohlstedt's research interests involve describing mesoscale phenomena such as charge transfer in photovoltaic materials, plasmon coupling of self-assembled metal nanostructures, and anisotropic cluster growth, using computational and theoretical frameworks. He uses a variety of approaches to study not only the phenomena of interest, but also the energetics and kinetics of the molecular assemblies. Techniques used to describe the phenomena include molecular dynamics, supervised machine learning, semiclassical dynamics, DFT, Monte Carlo, and lattice-based electrodynamics solvers.