Stephane Mallat
Stephane Mallat works on the mathematics of signal processing and statistical learning. He earned a doctorate at Pennsylvania in 1988 and held appointments at New York University, École Polytechnique, ENS, and the Collège de France. He developed multiresolution wavelet methods and worked on sparse representations. His 2011 Group Invariant Scattering paper studies representations that preserve useful information while controlling sensitivity to transformations. He held the Data Science chair at the Collège de France from 2017.
- Now at
- Collège de France
- Works
- 310
- Citations
- 80,189
- h-index
- 61
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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1988–1989
A mathematical basis for signals
Mallat completed his doctorate in electrical engineering at the University of Pennsylvania in 1988. He published two papers in 1989 on multiresolution approximation and wavelet representations.
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1995–2012
Applied mathematics in France
He was a professor of applied mathematics at École Polytechnique from 1995 to 2012. He also founded and led Let It Wave as chief executive from 2001 to 2007. These appointments connect academic work with signal processing applications.
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2011
Scattering representations
In Group Invariant Scattering, Mallat studied a representation built from wavelet operations. The paper addresses invariance to transformations and stability under deformations. It provides a mathematical way to examine features used for recognition.
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2012–2017
ENS and a Data Science chair
Mallat held a professorship at ENS from 2012 to 2017. He became professor for the Data Science chair at the Collège de France in 2017. His career links signal processing mathematics with questions about learning from complex data.
Sources and credits
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