Virginia Smith is an assistant professor in the Machine Learning Department at Carnegie Mellon University, and a courtesy faculty member in the Electrical and Computer Engineering Department. Her research interests lie at the intersection of machine learning, optimization, and computer systems. A unifying theme of her research is to develop machine learning methods and theory that effectively leverage prior knowledge and account for practical constraints (e.g., hardware capabilities, network capacity, statistical structure). Specific topics include: large-scale machine learning, distributed optimization, resource-constrained learning, multi-task learning, transfer learning, and data augmentation.