About me
Madeleine Udell is a postdoctoral fellow at Caltech's Center for the Mathematics of Information, hosted by Joel Tropp. She will be joining Cornell as an Assistant Professor in the School of Operations Research and Information Engineering in July 2016. Her research focus is on modeling and solving large-scale optimization problems and on finding and exploiting structure in high dimensional data, with applications in marketing, demographic modeling, and medical informatics. 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. Madeleine completed her PhD at Stanford University in Computational & Mathematical Engineering in 2015 under the supervision of Professor Stephen Boyd. 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.
