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Prize Spotlight: Emmanuel Candès

Emmanuel Candès
SIAM awarded the 2017 Ralph E. Kleinman Prize to Emmanuel Candès of Stanford University at the SIAM Annual Meeting held July 10-14, 2017 in Pittsburgh, PA.

SIAM awards the Ralph E. Kleinman Prize biennially to an individual for outstanding research, or other contributions, that bridge the gap between mathematics and applications. The prize recognizes work that uses high-level mathematics and/or invents new mathematical tools to solve applied problems from engineering, science, and technology. The value of the work is measured by the quality of the mathematics and its impact on the application.

The 2017 award of the Kleinman Prize recognizes Candès for fundamental breakthroughs in information theory, signal processing, imaging, computational harmonic analysis, and their applications to daily life problems in engineering and in physical and biomedical sciences.

Emmanuel Candès is the Barnum-Simons Chair in Mathematics and Statistics, and Professor of Electrical Engineering (by courtesy) at Stanford University, where he currently chairs the Department of Statistics. His work lies at the interface of mathematics, statistics, information theory, signal processing and scientific computing, and is about finding new ways of representing information and of extracting information from complex data. Candès graduated from École Polytechnique in 1993 with a degree in science and engineering, and received his PhD in statistics from Stanford University in 1998. He received the 2010 George Pólya Prize in Mathematics from SIAM and the 2015 AMS-SIAM George David Birkhoff Prize in Applied Mathematics. He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences.

Q: Why are you excited about winning this prize?

A: The kind of research I have always found the most challenging is that of pioneering novel mathematical abstractions in connection with real applications. I especially appreciate receiving the Ralph E. Kleinman Prize since this award specifically recognizes contributions bridging the gap between mathematics and applications. Much of my work over the years has been done in collaboration with colleagues and students, and I feel they also deserve a share of this prize as they have greatly improved me as a scientist.

I am also humbled by the fact that my colleagues took time away from their schedules to nominate me for this award without my knowledge. They thought I was a worthy candidate and this means a great deal to me.

Q: What does your research mean to the public?

A: I have been very fortunate to see some of my ideas being applied, bringing about some significant technological improvement. For instance, compressed sensing techniques have dramatically advanced the capabilities of magnetic resonance imaging (MRI) and are implemented in the newest generation of MR scans. I would also like to mention the impact of these techniques on pediatric diagnosis thanks to the wonderful work of Michael Lustig, John Pauly, Shreyas Vasanawala and their colleagues. These people have made a huge difference. 

In the big data era, researchers mine large data sets relentlessly in search of new discoveries. At the same time, it has been observed that science has, to some extent, run into the problem of irreproducibility. I regard this as a serious issue, and some of my recent work is about developing new statistical tools and theories to address some aspects, but of course not all, of this 'reproducibility crisis.'

Q: Could you tell us a bit about the research that won you the prize?

A: The theory of compressed sensing played a role in this. This theory states that most signals of interest can be acquired using far fewer samples than traditionally thought; for instance, with fewer samples than the Shannon-Nyquist theory dictates. This theory has profound consequences for data acquisition and underlies the recent great progress in magnetic resonance imaging I discussed above.

Q: What does being a SIAM member mean to you?

A: I treasure belonging to a community that values and shares knowledge. I also admire the unique way in which SIAM welcomes younger members. For instance, when I was at Caltech, I remember that Laurent Demanet along with others started a SIAM Student Chapter and the immediate positive impact this activity had on graduate students. 

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