Carnegie Mellon University

Virginia Smith

Virginia Smith

Assistant Professor, Electrical and Computer Engineering

Address 5000 Forbes Avenue
Pittsburgh, PA 15213


Virginia Smith is an assistant professor in Electrical and Computer Engineering at Carnegie Mellon University, and an affiliated faculty member in the Machine Learning Department. Her research interests include machine learning, optimization, and distributed systems. She has been the recipient of the NSF Graduate Research Fellowship, Google Anita Borg Memorial Scholarship, NDSEG Fellowship, and MLConf Industry Impact Award. Prior to CMU, Virginia received a Ph.D. from UC Berkeley and undergraduate degrees from the University of Virginia.


Virginia Smith's 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: distributed optimization, large-scale machine learning, resource-constrained learning, multi-task learning, transfer learning, and data augmentation.


  • Large-scale machine learning and distributed optimization
  • Optimization framework for distributed machine learning (CoCoA), Apache Spark and Google’s TensorFlow