Hugo Koubbi
PhD student in applied mathematics, with applications to neural networks.
I am a PhD student in mathematics, affiliated with CEREMADE, LJLL, and the Inria team MEGAVOLT. I am supervised by Borjan Geshkovski and Antonin Chambolle.
My research lies in applied mathematics, at the interface of probability, mean-field limits, and machine learning theory. I am particularly interested in the mathematical analysis of neural networks, with a focus on architectural aspects of modern machine learning models, especially Transformer architectures.
Before starting my PhD, I obtained a Master’s degree in Probability and Statistics from Université Paris-Saclay. I also spent the academic year 2024–2025 at Yale University, under the supervision of Theodor Misiakiewicz.
You can also find me on Google Scholar.