This research project aims to develop new models, theory, and algorithms for dynamic optimization model problems that incorporate robustness for the underlying probability distributions. We focus our work on the important classes of multistage stochastic problems, in which information is revealed period by period and decisions are made accordingly, using information from previous stages.