Research

My research develops mathematical theory to understand and improve modern data science and machine learning methods. I use tools from stochastic geometry, convex geometry, and probability theory to analyze and design new models and algorithms for extracting information from high-dimensional and noisy data. A list of my publications is available here.

Random tessellations

Random tessellations + machine learning

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Star geometry

Star geometry + regularizer learning

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Point processes

Point processes + applications

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Structured convex bodies

Structured convex bodies + applications

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