Dr. Stéphane Mallat stands as a preeminent figure in applied mathematics whose theoretical innovations have revolutionized signal processing and data science. Currently serving as Professor at the Collège de France where he holds the Data Sciences chair since 2017 he also maintains his position at the Computer Science Department of École normale supérieure where he has been a faculty member since 2012. Born in Suresnes on October 24 1962 Mallat completed his education at École polytechnique in 1981 before earning his PhD from the University of Pennsylvania in 1988 establishing the foundation for his groundbreaking contributions to mathematical signal analysis. His distinguished academic career includes presiding over the applied mathematics department at École polytechnique from 1998 to 2001 and serving as professor there until 2012 during which time he solidified his reputation as a visionary in mathematical approaches to signal processing.
Mallat's seminal contributions to wavelet theory building upon Yves Meyer's foundational work revolutionized harmonic analysis and signal processing creating mathematical tools that have become indispensable across numerous scientific and engineering applications. His theoretical framework has enabled dramatic advances in image compression noise reduction and feature extraction with applications spanning medical imaging telecommunications and geophysics fundamentally changing how scientists analyze complex data streams. The mathematical elegance and practical utility of his work on multiscale representations and sparse signal processing has generated extensive influence across multiple disciplines and inspired generations of researchers in both theoretical mathematics and applied engineering fields. Currently Mallat has pivoted his formidable mathematical expertise toward understanding the theoretical foundations of artificial intelligence focusing on mathematical modeling of neural networks to explain the mechanisms behind deep learning's remarkable effectiveness.
As a member of both the French Académie des sciences and Académie des technologies as well as the U.S. National Academy of Engineering Mallat has profoundly shaped the direction of mathematical research and its applications across multiple continents and disciplines. His leadership extends beyond research as he continues to mentor emerging scholars at the Collège de France and École normale supérieure cultivating the next generation of mathematical scientists who bridge theoretical rigor with practical applications. In 2025 his extraordinary career was crowned with the CNRS Gold Medal France's highest scientific honor recognizing both his past revolutionary contributions and his ongoing work to establish mathematical foundations for artificial intelligence. Mallat's current research seeks to develop comprehensive mathematical frameworks that explain why deep learning works so effectively potentially unlocking new paradigms in artificial intelligence that combine the power of neural networks with rigorous theoretical understanding.
