Stéphane Mallat was born onOctober24 1962. He graduated from the École polytechnique in 1981, went on to obtain a Ph.D. from the University of Pennsylvania in 1988, and defended his habilitation thesis in mathematics at the Université de Paris-Dauphine in 1992.
He was Professor of Mathematics and Computer Science at New York University's Courant Institute from 1998 to 1995, then returned to France as Professor of Applied Mathematics at École Polytechnique until 2012. He chaired the same department from 1998 to 2001. In 2001, he co-founded a start-up, Let it Wave, which he ran until 2007. He became a professor at the École normale supérieure de la rue d'Ulm from 2012 to 2017, then was appointed professor at the Collège de France in 2017, holding the Data Sciencechair.

Stéphane Mallat's research focuses on mathematics applied to signal processing and statistical learning. In particular, he introduced multiresolution theory to build wavelet bases, as well as the fast wavelet transform, from which the JPEG-2000 image compression standard was derived. He is the originator of parsimony representations by matching pursuit in dictionaries, for data processing. He is now working on the mathematical modeling of neural networks. He is a member of the US Academy of Sciences, Academy of Technology and National Academy of Engineering.