Leads a team in researching machine learning, particularly focusing on assessing and improving the robustness of deep learning systems, building complex modules (such as optimization solvers) within the loop of deep architectures, and developing new types of architectures for deep networks.
Background
Professor at Carnegie Mellon University; Director of the Machine Learning Department; research interests are broad, including making deep learning algorithms more robust, safer, and understanding how data impacts how models function.