Virginia Smith
Leonardo Associate Professor, Machine Learning
Courtesy Appointment, Electrical and Computer Engineering
Leonardo Associate Professor, Machine Learning
Courtesy Appointment, Electrical and Computer Engineering
Virginia Smith is the Leonardo Associate Professor of Machine Learning at Carnegie Mellon University, and an affiliated faculty member in the Department of Electrical and Computer Engineering. Her research interests include machine learning, optimization, and distributed systems. Prior to CMU, Virginia received a Ph.D. from UC Berkeley and undergraduate degrees from the University of Virginia.
2017 MS, Computer Science, University of California, Berkeley
2017 Ph.D., Computer Science, University of California, Berkeley
2012 BA, Computer Science, University of Virginia
2012 BA, Mathematics, University of Virginia
CyLab Security and Privacy Institute
This year, CyLab has awarded $400K in seed funding to 17 CMU students, faculty, and staff members representing five departments at the university.
Carnegie Bosch Institute
Virginia Smith and Steven Wu actively collaborate in the area of federated learning, creating provable and deployable architectures to enable privacy-preserving machine learning across distributed data silos. Lack of privacy can be a bottleneck for adoption of future machine learning systems. Research towards privacy enhancing technologies is the central focus of the work of CBI fellow Pratiksha Thaker with Smith and Wu.
Engineering and Public Policy
Virginia Smith, an assistant professor in the Machine Learning Department, and Priya Donti, a Ph.D. candidate in the Computer Science and Engineering and Public Policy departments, have been named to MIT Technology Review’s prestigious annual list of Innovators Under 35.
CMU Engineering
Researchers from Carnegie Mellon University’s College of Engineering share what they have learned about artificial intelligence while working in the field.