Ali Mohammad-Djafari received the B.Sc. degree in electrical engineering from Polytechnique of Teheran, in 1975, the diploma degree (M.Sc.) from Ecole Supérieure d'Electricité (SUPELEC), Gif sur Yvette, France, in 1977 and the "Docteur-Ingénieur" (Ph.D.) degree and "Doctorat d'Etat" in Physics, from the University of Paris Sud 11 (UPS), Orsay, France, respectively in 1981 and 1987.
He was Associate Professor at UPS for two years (1981-1983). Since 1984, he has a permanent position at "Centre National de la Recherche Scientifique (CNRS)" and works at "Laboratoire des Signaux et Systèmes (L2S)" at Supélec. He was a visiting Associate Professor at University of Notre Dame, Indiana, USA during 1997-1998. From 1998 to 2002, he has been at the head of Signal and Image Processing division at this laboratory. Presently, he is "Directeur de recherche" and his main scientific interests are in developing new probabilistic methods based on Bayesian inference, Information Theory and Maximum Entropy approaches for Inverse Problems in general, and more specifically in imaging and vision: image reconstruction, signal and image deconvolution, blind source separation, data fusion, multi and hyperspectral image segmentation. The main application domains of his interests are Computed Tomography (X rays, PET, SPECT, MRI, microwave, ultrasound and eddy current imaging) either for medical imaging or for non destructive testing (NDT) in industry.
He was Associate Professor at UPS for two years (1981-1983). Since 1984, he has a permanent position at "Centre National de la Recherche Scientifique (CNRS)" and works at "Laboratoire des Signaux et Systèmes (L2S)" at Supélec. He was a visiting Associate Professor at University of Notre Dame, Indiana, USA during 1997-1998. From 1998 to 2002, he has been at the head of Signal and Image Processing division at this laboratory. Presently, he is "Directeur de recherche" and his main scientific interests are in developing new probabilistic methods based on Bayesian inference, Information Theory and Maximum Entropy approaches for Inverse Problems in general, and more specifically in imaging and vision: image reconstruction, signal and image deconvolution, blind source separation, data fusion, multi and hyperspectral image segmentation. The main application domains of his interests are Computed Tomography (X rays, PET, SPECT, MRI, microwave, ultrasound and eddy current imaging) either for medical imaging or for non destructive testing (NDT) in industry.
View contact details
