Grace Wahba

Grace Wahba

Grace Wahba (born August 3, 1934) is the I. J. Schoenberg Professor of Statistics at the University of Wisconsin-Madison. She is a pioneer in methods for smoothing noisy data, where the problem is to balance a smooth fit against loss of information. Best known for the Generalized Cross Validation Technique and "Wahba's problem", she and her students have developed methods with application in demographic studies, machine learning, medical imaging, and climate prediction. She was educated at Cornell (B.A. 1956), University of Maryland, College Park (M.A. 1962) and Stanford (Ph.D. 1966), and worked in industry for several years before receiving her doctorate in 1966 and settling in Madison in 1967. She is the author of "Spline Models for Observational Data", [http://www.siam.org/books/ SIAM] , 1990. She waselected to the National Academy of Sciences in 2000 and received an honorary Degree of Doctor of Science from the University of Chicago in 2007.

Her work has influenced applied science in the areas of risk modeling, magnetic resonance imaging, meteorology, DNA microarrays, and satellite imaging.

External links

* [http://www.stat.wisc.edu/~wahba/ Grace Wahba's University of Wisconsin website Home page]


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