David Donoho is a mathematician who has made fundamental contributions to theoretical and computational statistics, as well as to signal processing and harmonic analysis. Anne T. and Robert M. Bass Professor in the Humanities and Sciences. Professor of Statistics. Stanford University. NSF Postdoctoral Fellow, Department of Statistics, University of. David Donoho is a data scientist who had revolutionised the field, particularly with his concept of compressed sensing. He has received many awards including the Norbert Wiener Prize in Applied Mathematics 2010 and the Shaw Prize in Mathematics 2013.
David Donoho is a data scientist who had revolutionised the field, particularly with his concept of compressed sensing. He has received many awards including the Norbert Wiener Prize in Applied Mathematics 2010 and the Shaw Prize in Mathematics 2013. David Donoho is world-renowned for many important contributions to statistics and its applications to image and signal processing, in particular to the retrieval of essential information from “sparse” data. David Donoho is a statistician whose work ranges from statistical computing to classical mathematical analysis. His theoretical work includes the nonlinear recovery of signals despite massively incomplete data; recovery of curves from noisy statistical data in a theoretically optimum manner; and robust methods for treating severely contaminated ... David Donoho is the Anne T. and Robert M. Bass Professor of Humanities and Sciences and Professor of Statistics at Stanford University. He has made fundamental contributions to theoretical and computational statistics, and his algorithms have contributed significantly to our understanding of how to work with sparse data. Princeton alum David Donoho '78, Stanford's Anne T. and Robert M. Bass Professor in the School of Humanities and Sciences, was awarded the 2018 Carl Friedrich Gauss Prize at the International Congress of Mathematicians in Rio de Janeiro for his fundamental contributions to the mathematical, statistical and computational analysis of important ...
David Donoho is a statistician whose work ranges from statistical computing to classical mathematical analysis. His theoretical work includes the nonlinear recovery of signals despite massively incomplete data; recovery of curves from noisy statistical data in a theoretically optimum manner; and robust methods for treating severely contaminated ... David Donoho is the Anne T. and Robert M. Bass Professor of Humanities and Sciences and Professor of Statistics at Stanford University. He has made fundamental contributions to theoretical and computational statistics, and his algorithms have contributed significantly to our understanding of how to work with sparse data. Princeton alum David Donoho '78, Stanford's Anne T. and Robert M. Bass Professor in the School of Humanities and Sciences, was awarded the 2018 Carl Friedrich Gauss Prize at the International Congress of Mathematicians in Rio de Janeiro for his fundamental contributions to the mathematical, statistical and computational analysis of important ... David Donoho has studied the exploitation of sparse signals in signal recovery, including for denoising, superresolution, and solution of underdetermined equations.