Grace Wahba
| Grace Wahba | |
|---|---|
| Born | August 3, 1934 |
| Nationality | American |
| Fields | Mathematics, Statistics, Machine Learning |
| Institutions | University of Wisconsin–Madison |
| Alma mater |
Stanford University University of Maryland, College Park Cornell University |
| Doctoral advisor | Emanuel Parzen |
| Doctoral students | |
| Known for | generalized cross validation, smoothing splines |
Grace Wahba (born August 3, 1934) is the I. J. Schoenberg-Hilldale Professor of Statistics at the University of Wisconsin–Madison. She is a pioneer in methods for smoothing noisy data. Best known for the development of generalized cross-validation and "Wahba's problem", she has developed methods with applications in demographic studies, machine learning, DNA microarrays, risk modeling, 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. She was elected to the United States National Academy of Sciences in 2000 and received an honorary degree of Doctor of Science from the University of Chicago in 2007.
Wahba is a member of the National Academy of Sciences, and a fellow of several academic societies including the American Academy of Arts and Sciences, the American Association for the Advancement of Science, the American Statistical Association, and the Institute of Mathematical Statistics. Over the years she has received a selection of notable awards in the statistics community:
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