Stéphane Mallat

Stéphane Mallat is a Professor and Chair in Data Science at the Collège de France. He graduated from École Polytechnique in 1981, earned a Ph.D. in electrical engineering from the University of Pennsylvania in 1988, and completed his habilitation in mathematics at Université Paris-Dauphine in 1992. He served as Professor of Mathematics and Computer Science at the Courant Institute of Mathematical Sciences, New York University, from 1988 to 1995. He then returned to France as Professor of Applied Mathematics at École Polytechnique, where he chaired the department from 1998 to 2001 and remained until 2012. In 2001, he co-founded the start-up Let It Wave, which he led until 2007. From 2012 to 2017, he was a Professor at École Normale Supérieure (rue d’Ulm), before being appointed to the Collège de France. Prof. Mallat’s research focuses on mathematical approaches to signal processing and statistical learning. He introduced multiresolution theory for constructing wavelet bases and developed the fast wavelet transform, which contributed to the JPEG-2000 image compression standard. He pioneered sparse representations using matching pursuit in dictionaries for data processing and is currently working on the mathematical modeling of neural networks. He is a Fellow of the IEEE and a member of the U.S. National Academy of Sciences, the French Academy of Technologies, and the U.S. National Academy of Engineering. His numerous awards and recognitions include the Blaise Pascal Prize from the French Academy of Sciences, the SPIE Outstanding Achievement Award, the European Academies’ Information Technology Grand Prize, the EADS Grand Prix, the IEEE Sustained Impact Award, the IEEE Carl Friedrich Gauss Prize, the Milner Award of the Royal Society, the IEEE Fourier Award, and the CNRS Gold Medal.