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Princess of Asturias Award for Technical & Scientific Research 2020
Yves Meyer (French), Ingrid Daubechies (Belgian and American), Terence Tao (Australian and American), and Emmanuel Candès (French) have made immeasurable, ground-breaking contributions to modern theories and techniques of mathematical data and signal processing. These constitute the foundations and backbone of the digital age (by enabling the compression of graphic files with little loss of resolution), of medical imaging and diagnosis (by enabling accurate images to be reconstructed from a small number of data) and of engineering and scientific research (by eliminating interference and background noise). As regards this last point, these techniques serve as the key, for example, to the deconvolution of Hubble Space Telescope images and have been crucial in the detection by LIGO of gravitational waves resulting from the collision of two black holes. The outstanding contributions of these world leaders in mathematics to modern mathematical data and signal processing are essentially based on two different yet complementary tools: wavelets and compressed sensing or matrix completion.
Yves Meyer and Ingrid Daubechies have led the development of modern mathematical wavelet theory, located at the overlap between mathematics, information technology and computer science. After making important contributions to number theory early on in his career, Meyer began working on methods to divide complex mathematical objects into simpler, wave-like components, which is known as harmonic analysis. In 1984, Meyer read the studies that Jean Morlet, Alex Grossmann and Ingrid Daubechies had carried out on wavelets, which sparked his interest in this field. Mathematical wavelet theory enables images and sounds to be decomposed into mathematical fragments, which capture irregularities in the pattern, while at the same time being manageable. This technique underlies data compression and storage and noise suppression. Together with Daubechies, Meyer brought together previous studies and related them to the analytical tools used in harmonic analysis. This discovery later led to Meyer’s demonstration that waves can form mutually independent sets of mathematical objects called orthogonal bases. His work inspired Daubechies to construct orthogonal wavelets with compact support, and later biorthogonal wavelets, which revolutionized the field of engineering. Both worked on the development of wavelet packages, which allow improved adaptation to the particularities of a signal or image. They are currently found in numerous technologies, such as digital image compression, and are used in the JPEG 2000 format.
A second revolution in data and signal processing techniques came in the first decade of the 21st century with the development of the theories of compressed sensing or compressive sampling and matrix completion, fruit of the collaboration between Terence Tao and Emmanuel Candès. This work enables the efficient reconstruction of scattered data based on very few measurements. One of the core issues in medical imaging and, in general, in all areas of signal processing, is how to reconstruct a signal from partial, noisy measurements. Advanced reconstruction techniques, such as compressed sensing and matrix completion, enable the number of required samples to be reduced, which in medical imaging means being able to examine the patient faster. For example, the scanners currently used in magnetic resonance imaging techniques have implemented this mathematical tool, making it possible to shorten the patient’s scanning or exposure time and subsequently reconstruct the image without loss of quality. Other low-quality images from other areas can also be efficiently reconstructed using this technique. In short, the compressed sensing technique has contributed significantly to signal processing by enabling the compressed version of a signal to be reconstructed using a small number of linear measurements. This means a lower sampling frequency, less data, less use of storage resources, decreased speed requirements for analog-to-digital converters and less time required for data transmission. These mathematical theories developed by Yves Meyer, Ingrid Daubechies, Terence Tao and Emmanuel Candès highlight the unifying and cross-cutting role of mathematics in different scientific and engineering disciplines, with practical solutions applicable in multiple fields, as well as constituting an example of the usefulness of work in pure mathematics.
Yves Meyer (France, 19th July 1939) graduated in Mathematics from École Normale Supérieure de Paris (ENS) and earned his PhD from the University of Strasbourg in 1966. That same year he obtained a position as professor of Mathematics at Paris-Sud University, where he remained until 1980. He was subsequently a professor at the École Polytechnique (1980-1986) and Paris-Dauphine University (1986-1995). In 1995, he moved to the Centre for Mathematics and Applications (CMLA) at École Normale Supérieure Cachan (recently renamed ENS Paris-Saclay), where he worked until he officially retired in 2008, although he remains an associate professor emeritus at this centre. Meyer is a member of the French Academy of Science, the American Academy of Arts and Sciences, the United States National Academy of Sciences, the American Mathematical Society, and has been a speaker at various international mathematics conferences. Outstanding among the awards he has received throughout his career is the Abel Prize (Norway, 2017), one of the most important awards in mathematics. He also holds the Salem Prize (1970) and the Gauss Prize (2010), the latter jointly awarded by the International Mathematical Union.
Ingrid Daubechies (Houthalen, Belgium, 17th August 1954) graduated in Physics from the Free University of Brussels (ULB) in 1975, where she earned her PhD in Theoretical Physics five years later. She was a research assistant and then research professor in the Physics Department of this same university until 1987, the year in which she began working at the AT&T Bell Laboratories Mathematical Research Center in New Jersey (USA), where she remained until 1994. From 1991 to 1994, she concurrently held the position of professor in the Department of Mathematics, Rutgers University. She was a professor in the Department of Mathematics at Princeton University between 1994 and 2011, and currently holds the James B. Duke Chair at Duke University. She has published more than a hundred scientific articles, her publications have been cited 92 392 times, with an h-index of 75. She is a member of the American Academy of Arts and Sciences, the United States National Academy of Sciences, the Royal Netherlands Academy of Arts and Sciences, the American Philosophical Society, the London Mathematical Society and the Paris Academy of Sciences. In addition, she holds honorary degrees from several universities and has been the first woman to win the Frederic Esser Nemmers Prize in Mathematics (USA, 2012) and the first to preside the International Mathematical Union. Among other distinctions, she has received the Ruth Lyttle Satter Prize in Mathematics (USA, 1977), the National Academy of Sciences Medal in Mathematics (USA, 2000) and the Benjamin Franklin Medal in Electrical Engineering (USA, 2011).
Terence Tao (Adelaide, Australia, 17th July 1975) graduated in Mathematics from Flinders University in 1991 and a year later obtained his Master’s degree from this same university. He earned his PhD in Mathematics from Princeton University in 1996. That same year, he became an assistant professor at the University of California at Los Angeles (UCLA), an institution where he currently works as a full professor. Tao’s papers have been cited 74 830 times, with an h-index of 95. He is a member of the Australian Academy of Science, the United States National Academy of Sciences, the American Academy of Arts and Sciences and the American Mathematical Society. He has authored 17 books and has received, among other awards, the Salem Prize (2000), the Bôcher Prize (USA, 2002), the American Mathematical Society’s Levi L. Conant Prize (2005) and the International Mathematical Union Fields Medal (2006), one of the most important awards in this field, for his contributions to partial differential equations, combinatorics, harmonic analysis and additive number theory. He is the person with the highest IQ in the world, measured at 230.
Emmanuel Candès (Paris, France, 27th April 1970) received his BSc in Engineering from École Polytechnique, Paris, in 1993, and earned his PhD in Statistics from Stanford University in 1998. He has been a professor of Applied and Computational Mathematics and Ronald and Maxine Linde Professor at the California Institute of Technology (Caltech). In 2009, he began working at Stanford University, where he is currently Barnum-Simon Professor of Mathematics and Statistics, Professor of Electrical Engineering and Co-Director of the Data Science Institute. Candès’ publications have been cited 125 108 times, with an h-index of 89. He has received numerous awards throughout his career, most notably the Alan T. Waterman Award (USA, 2006), the James H. Wilkinson Prize in Numerical Analysis and Scientific Computing (2005) and the 2010 George Pólya Prize –shared with Terence Tao–, both awarded by the Society for Industrial and Applied Mathematics (SIAM), as well as the Collatz Prize (2011), awarded by the International Council of Industrial and Applied Mathematics (ICIAM). He has given more than 50 plenary lectures at major international conferences and is a member of the United States National Academy of Sciences and the American Academy of Arts and Sciences.
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