2018 - Rolf Schock Prize for Mathematics
2002 - Fellow of the American Association for the Advancement of Science (AAAS)
1999 - US President's National Medal of Science "For his fundamental contributions to pure mathematics in the field of harmonic analysis, and for his achievements in the adaptation of that field to the capabilities of the digital computer to produce a family of fast, robust computational tools that have substantially benefited science and technology.", Presented by President William Clinton in a White House (East Room) ceremony on Tuesday, March 14, 2000.
1998 - Member of the National Academy of Sciences
1994 - Fellow of the American Academy of Arts and Sciences
1970 - Fellow of Alfred P. Sloan Foundation
The scientist’s investigation covers issues in Mathematical analysis, Pure mathematics, Wavelet, Artificial intelligence and Discrete mathematics. His Mathematical analysis research integrates issues from Eigenvalues and eigenvectors and Applied mathematics. The various areas that Ronald R. Coifman examines in his Wavelet study include Algorithm and Signal processing.
His Algorithm study combines topics from a wide range of disciplines, such as Orthonormal basis, Wavelet transform and Euclidean geometry. In Artificial intelligence, he works on issues like Pattern recognition, which are connected to Basis function, Information extraction, Pixel and Pattern matching. In the field of Discrete mathematics, his study on Characterization overlaps with subjects such as Real variable.
His primary scientific interests are in Artificial intelligence, Algorithm, Wavelet, Pattern recognition and Mathematical analysis. His Artificial intelligence study incorporates themes from Orthonormal basis, Machine learning and Computer vision. His Orthonormal basis study combines topics in areas such as Basis function and Linear discriminant analysis.
As part of the same scientific family, Ronald R. Coifman usually focuses on Algorithm, concentrating on Nonlinear dimensionality reduction and intersecting with Metric. His studies deal with areas such as Image processing, Basis and Signal processing as well as Wavelet. His work in Mathematical analysis addresses subjects such as Pure mathematics, which are connected to disciplines such as Type.
His primary areas of study are Algorithm, Metric, Nonlinear dimensionality reduction, Pure mathematics and Biological data. His Algorithm research incorporates themes from Embedding, Matrix, Earth mover's distance, Manifold and Graph. His work carried out in the field of Metric brings together such families of science as Data-driven, Row, Cluster analysis and Pattern recognition.
His Pure mathematics research includes elements of Function, Wavelet and Dimension. His Wavelet study which covers Hardy space that intersects with Invariant subspace, Linear subspace and Fourier analysis. To a larger extent, Ronald R. Coifman studies Mathematical analysis with the aim of understanding Holomorphic function.
His scientific interests lie mostly in Metric, Algorithm, Biological data, Visualization and Embedding. While the research belongs to areas of Metric, Ronald R. Coifman spends his time largely on the problem of Pattern recognition, intersecting his research to questions surrounding Network complexity and Premovement neuronal activity. The various areas that Ronald R. Coifman examines in his Algorithm study include Nonlinear dimensionality reduction, Diffusion map, Matrix, Anomaly detection and Data set.
The concepts of his Biological data study are interwoven with issues in Identification, Structure, Range, Artificial intelligence and Big data. His Embedding research integrates issues from Space, Point, Extension and Euclidean geometry. His Manifold research is included under the broader classification of Pure mathematics.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Entropy-based algorithms for best basis selection
R.R. Coifman;M.V. Wickerhauser.
IEEE Transactions on Information Theory (1992)
R. R. Coifman;D. L. Donoho.
Lect. Notes Stat. (1995)
Fast wavelet transforms and numerical algorithms I
G. Beylkin;R. Coifman;V. Rokhlin.
Communications on Pure and Applied Mathematics (1991)
Analyse harmonique non-commutative sur certains espaces homogènes : étude de certaines intégrales singulières
Ronald R. Coifman;Guido L. Weiss.
Extensions of Hardy spaces and their use in analysis
Ronald R. Coifman;Guido Weiss.
Bulletin of the American Mathematical Society (1977)
The fast multipole method for the wave equation: a pedestrian prescription
R. Coifman;V. Rokhlin;S. Wandzura.
IEEE Antennas and Propagation Magazine (1993)
Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps
R. R. Coifman;S. Lafon;A. B. Lee;M. Maggioni.
Proceedings of the National Academy of Sciences of the United States of America (2005)
Factorization theorems for Hardy spaces in several variables
R. R. Coifman;R. Rochberg.
Annals of Mathematics (1976)
Weighted norm inequalities for maximal functions and singular integrals
R. R. Coifman;C. Fefferman.
Studia Mathematica (1974)
Au delà des opérateurs pseudo-différentiels
Ronald R. Coifman;Yves Meyer.
Applied and Computational Harmonic Analysis
(Impact Factor: 2.974)
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