Contact: sl8160@nyu.edu

Bio: Sanae is a PhD student at the NYU Center for Data Science and a DeepMind fellow, advised by Professor Andrew Wilson. She is currently interested in understanding and quantifying the generalization of deep learning models. More broadly, her research interests include the mathematics of deep learning, probabilistic generative models, Bayesian learning and statistical learning theory. Before joining NYU, Sanae obtained a master’s degree in applied mathematics from Polytechnique Montreal. She worked with Professors Andrea Lodi and Dominique Orban to design stochastic first- and second-order algorithms with compelling theoretical and empirical properties for machine learning and large-scale optimization. She also holds an engineering degree in applied mathematics from CentraleSupélec in France.

Awards: 

• DeepMind Fellowship

• Microsoft Research PhD Fellowship