Madeleine Udell

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a picture of Madeleine
Photo by Diana Mellon

I am a PhD candidate in Computational & Mathematical Engineering at Stanford University, working with Professor Stephen Boyd. I am interested in modeling and solving large-scale optimization problems, and in finding and exploiting structure in high dimensional data. My methodological interests are driven by the framework of convex optimization and of graph theory, which provide powerful tools for formalizing objectives in statistics and machine learning.

I am currently working on applications of and algorithms for Generalized Low Rank Models, which extend principal components analysis (PCA) to embed arbitrary data sets consisting of numerical, Boolean, categorical, ordinal, and missing data into a low dimensional space. My other favorite problems to ponder include how to parallelize optimization algorithms for general cone programs, ways to use graph partitioning to improve the convergence of distributed optimization algorithms, and how to decide which entry to query next in a matrix-completion setting.


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