I am interested in advancing our scientific understanding of deep learning and using theoretical insights to design methods which work well in practice. My current focus is characterizing the generalization phenomena of overparameterized neural networks and developing provable algorithms for robust learning, particularly under distribution shift. The ultimate goal of my research is to enable the safe and trusted deployment of deep learning systems in high-consequence applications such as medicine, defense, and energy.