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MU

Madeleine Udell

Cornell University
Assistant Professor
Madeleine Udell is Assistant Professor of Operations Research and Information Engineering and Richard and Sybil Smith Sesquicenteial Fellow at Cornell University. She studies optimization and machine learning for large scale data analysis and control, with applications in marketing, demographic modeling, medical informatics, and engineering system design. Her recent work on generalized low rank models (GLRMs) extends principal components analysis (PCA) to embed tabular data sets with heterogeneous (numerical, Boolean, categorical, and ordinal) types into a low dimensional space, providing a coherent framework for compressing, denoising, and imputing missing entries. She has developed of a number of open source libraries for modeling and solving optimization problems, including Convex.jl, one of the top ten tools in the new Julia language for technical computing, and is a member of the JuliaOpt organization, which curates high quality optimization software.nMadeleine completed her Ph.D. at Stanford University in Computational & Mathematical Engineering in 2015 under the supervision of Stephen Boyd, and a one year postdoctoral fellowship at Caltech in the Center for the Mathematics of Information hosted by Professor Joel Tropp. At Stanford, she was awarded a NSF Graduate Fellowship, a Gabilan Graduate Fellowship, and a Gerald J. Lieberman Fellowship, and was selected as the doctoral student member of Stanford's School of Engineering Future Committee to develop a road-map for the future of engineering at Stanford over the next 10–20 years. She received a B.S. degree in Mathematics and Physics, summa cum laude, with honors in mathematics and in physics, from Yale University.

My Speakers Sessions

Friday, June 23
 

1:42pm PDT