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Ying Cui is an assistant professor in the Department of Industrial Engineering and Operations Research at the University of California, Berkeley. Her research focuses on the mathematical foundations of data science, with an emphasis on optimization techniques in operations research and machine learning. She explores computational methods in large-scale semidefinite programming and stochastic programming and engages with modern nonconvex nondifferentiable optimization problems. She also works on variational analysis and matrix optimization problems. Before joining Berkeley, she served as an assistant professor in the Department of Industrial and Systems Engineering at the University of Minnesota. Her research expertise includes continuous optimization, uncertainty, statistical estimations, and applications of artificial intelligence in data-driven contexts.
The Mathematics Subject GRE is required for the Fall 2026 admissions cycle. General GRE is optional.