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Theo is an Assistant Professor in the Department of Statistics and Data Science at Yale University. He researches the spectral geometry of discrete systems. Most often, he studies random matrices and random graphs using analytic and probabilistic methods. More broadly, he considers many questions in analysis and probability theory motivated by computer science and statistical physics.

What do you do with Data Science?

I work on questions related to the spectral theory of random matrices and random graphs, which serve as important abstractions of statistical systems. Spectral algorithms are fundamental tools for analyzing these models, making it crucial to understand the generic properties of their eigenvalues and eigenvectors. Some of my main results include determining the distribution of the largest eigenvalues of random regular graphs and proving Gaussian behavior of eigenvectors in generic sparse systems. I would like to compare these phenomena with those arising in other theoretical models that are ubiquitous in data science.

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