Title: Dynamical Models of Galaxy Mergers: Connecting Simulations and Data

Dynamical models of galaxy mergers can enable a detailed comparison of observations and predictions from simulations. This can shed light on processes thought to be important in galaxy evolution, including star formation and active galactic nuclei. I will show examples of newly derived dynamical models for IR luminous galaxy mergers and demonstrate a dynamically motivated merger stage classification based on these models. I will also show progress comparing simulated star formation from matched hydrodynamical simulations with observational tracers of star formation.