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Emmanuel Candès

Emmanuel Candès
Emmanuel Candès.jpg
Born (1970-04-27) 27 April 1970 (age 46)
Paris, France
Nationality French
Fields Statistician, Mathematician
Institutions Stanford University
California Institute of Technology
Alma mater Stanford University
École Polytechnique
Doctoral advisor David Donoho
Doctoral students Stephen Becker
Laurent Demanet
Carlos Fernandez-Granda
Xiaodong Li
Yaniv Plan
Paige Randall
Mahdi Soltanolkotabi
Vladislav Voroninski
Known for Wavelet theory, Curvelets, Compressed sensing
Notable awards

Alfred P. Sloan Research Fellowship (2001)
James H. Wilkinson Prize in Numerical Analysis and Scientific Computing (2005)
Alan T. Waterman Award (2006)
Vasil A. Popov Prize (2001)
Information Theory Society Paper Award (2008)
George Pólya Prize (2010)
Collatz Prize (ICIAM) (2011)
Lagrange Prize in Continuous Optimization (2012)

Dannie Heineman Prize (2013)

Alfred P. Sloan Research Fellowship (2001)
James H. Wilkinson Prize in Numerical Analysis and Scientific Computing (2005)
Alan T. Waterman Award (2006)
Vasil A. Popov Prize (2001)
Information Theory Society Paper Award (2008)
George Pólya Prize (2010)
Collatz Prize (ICIAM) (2011)
Lagrange Prize in Continuous Optimization (2012)

Emmanuel Jean Candès (born 27 April 1970) is a professor of mathematics, statistics, and electrical engineering (by courtesy) at Stanford University, where he is also the Barnum-Simons Chair in Mathematics and Statistics.

Candès earned a M.Sc. from the École Polytechnique in 1993. He did his graduate studies at Stanford, where he earned a Ph.D. in statistics in 1998 under the supervision of David Donoho and immediately joined the Stanford faculty as an assistant professor of statistics. He moved to the California Institute of Technology in 2000, where in 2006 he was named the Ronald and Maxine Linde Professor of Applied and Computational Mathematics. He returned to Stanford in 2009.

Candès' early research concerned nonlinear approximation theory. In his Ph.D. thesis, he developed generalizations of wavelets called curvelets and ridgelets that were able to capture higher order structures in signals. This work has had significant impact in image processing and multiscale analysis, and earned him the Popov prize in approximation theory in 2001.


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