Sébastien Bubeck

Sr. Principal Research Manager

Machine Learning Foundations, Microsoft Research, Redmond


Building 99, 3920

Redmond, WA 98052

sebubeck AT microsoft DOT com

I am a Sr. Principal Research Manager in the Machine Learning Foundations group at Microsoft Research (MSR). I joined the Theory Group at MSR in 2014, after three years as an assistant professor at Princeton University. In the first 15 years of my career I mostly worked on convex optimization, online algorithms and adversarial robustness in machine learning, and received several best paper awards for these works (STOC 2023, NeurIPS 2018 and 2021 best paper, ALT 2018 and 2023 best student paper in joint work with MSR interns, COLT 2016 best paper, and COLT 2009 best student paper).

I am now more focused on understanding how intelligence emerges in large language models, and how to use this understanding to improve LLMs’ intelligence, possibly towards building AGI. We call our approach “Physics of AGI”, as we try to uncover at different scales (parameters, neurons, group of neurons, layers, ect …) how the parts of the system come together to create the striking and unexpected behavior of these models. A good starting point to learn more is this video.