# Hugo Latourelle-Vigeant

Ph.D. student at Yale University - Department of Statistics and Data Science

Ph.D. student @ Yale University

Welcome to my academic website! I am an incoming Ph.D. student at Yale University’s Statistics and Data Science program. I recently completed my Master’s degree in Mathematics and Statistics at McGill University, where I had the privilege of working under the co-supervision of Professor Courtney Paquette and Professor Elliot Paquette. Prior to this, I earned my B.Sc. in Mathematics and Computer Science with First-Class Honours, also from McGill University.

My academic interests revolve around the fascinating realm of large random systems. I see data science and machine learning as exciting avenues for theoretical exploration, using tools from random matrix theory, high-dimensional probability, optimization and statistics, into the complexities of high-dimensional systems. My research has led me to study various aspects of random matrix theory, notably the matrix Dyson equation. I have also explored the applications of random matrix theory to machine learning, notably by establishing a Gaussian equivalence result for the empirical test error of random features ridge regression. For a slightly more detailed discussion, please refer to the “research” tab.

Beyond my academic pursuits, I like to engage in physical activities. Snorkeling, kayaking, and skiing are among my favorite pastimes. In an alternate reality, I might have been known as a “gym bro.”

## news

Jul 08, 2024 | Master's thesis published |
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Dec 13, 2023 | First paper! |

Dec 04, 2023 | Presentation at the 2023 Winter meeting of the Canadian Mathematical Society |

Sep 01, 2023 | Organizer for the Montreal RMT-ML-OPT Seminar |

Aug 01, 2023 | Princeton Machine Learning Theory Summer School |