Dallas Foster is a postdoctoral associate in the MIT Department of Aeronautics and Astronautics, as a member of the Uncertainty Quantification group within the Aerospace Computational Design Laboratory. Dallas’ research focuses on Bayesian inference techniques for data-driven physical models with additional research interests in data assimilation, scientific computing, and machine learning with applications to climate, geophysics, and chemistry. As part of the CESMIX project, he is developing Uncertainty Quantification techniques that couple probabilistic inference through quantum and molecular scales.