Madeleine Udell

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 a bound on the duality gap for separable non-convex optimization problems. I'm also working on a generalization of PCA to heterogeneous data (consisting of boolean and categorical variables as well as numerical data). 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 whether it's possible to speed up bandit learning by using ideas from matrix completion.

In my extracurricular life, I am also a classical harpist, a long-distance runner, and an intrepid cook.

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