Jean-Michel Morel

Professor at Ecole Normale Supérieure de Cachan,  Centre de Mathématiques et Leurs Applications (CMLA)
moreljeanmichel (at) gmail (dot) com
CMLA, ENS Cachan, 61, avenue du Président Wilson, 94235 Cachan cédex
Telephone:  contact me first by email


 Jean-Michel Morel leads a team of 20 researchers and coordinates 20 more on the mathematical analysis of image processing and the invention of new algorithms. This team collaborates with French Space Agency for the design of Earth observation satellites (SPOT5, Pleiades, OTOS).  The image denoising algorithms co-invented by JMM are implemented in more than 300 million cameraphones by DxO Labs, a world leader in software and hardware for cameras. In 2011 JMM founded Image Processing on Line (, the first journal publishing reproducible algorithms in online executable articles. IPOL has collaborators in 15 universities and its public archives contain 120000 online experiments. JMM’s recent awards: 2010 Clay Scholar in Residence, European Research Council advanced grant 2010, Grand Prix INRIA – French Academy of Science 2013.


Jean-Michel Morel has been in turn a PhD student at Université Paris IV, a postdoc at SISSA (Trieste, Italy), a teaching assistant at Université de Marseille Luminy, an assistant professor at Université Paris Dauphine, and is currently a professor at Ecole Normale Supérieure de Cachan. He has also been for 20 years a permanent visiting professor at Universitat Illes Balears (where he leads a six researchers team), and a recurrent invited professor at University of California at Los Angeles.


Jean-Michel Morel is a mathematician trained in nonlinear analysis with a PhD and a doctorat d’état on partial differential equations and variational methods under the guidance of Haïm Brezis. Then he developed an axiomatic theory of image analysis to derive and analyze the new PDEs and variational models arising in these fields. Working on the efficient numerical implementation of these algorithms, he has progressively become a specialist of image processing,  and has invented several algorithms now widespread in software and hardware. Interested in image analysis as well, he has proposed a statistical theory of perception inspired from Gestalt theory and psychophysics. This theory has also found applications for the automatic detection of objects in images.

In recent years, he has focused on the technological, methodological and editorial changes in applied mathematics required by the development of the web, namely the possibility to publish algorithms in online executable form.  To complete his exploration of images, Jean-Michel Morel proposes to develop mathematical models to classify the space of perceptual images. He will use computer graphics techniques to build image synthesis algorithms to explore abstract textures, shapes and images, and to develop a computational theory of decorative and abstract art.