Christine De Mol

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Christine De Mol (born 23 April 1954)[1] is a Belgian applied mathematician and mathematical physicist interested in inverse problems, regularization, wavelets, and machine learning, and known for her work on proximal gradient methods and the application of proximal gradient methods for learning. She is a professor of mathematics at the Université libre de Bruxelles, and the former chair of the SIAM Activity Group on Imaging Science.

De Mol was educated at the Université libre de Bruxelles, earning a licence in physics in 1975 and a Ph.D. in 1979, with a dissertation Sur la régularisation des problèmes inverses linéaires[1] under the joint supervision of Jean Reignier and Mario Bertero.[2]

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