Grace Wahba

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.

Awards and honors

Wahba is a member of the National Academy of Sciences,^[1] 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.^[2] Over the years she has received a selection of notable awards in the statistics community:

• R. A. Fisher Lectureship, COPSS, August 2014^[3]
• Gottfried E. Noether Senior Researcher Award, Joint Statistics Meetings, August 2009
• Committee of Presidents of Statistical Societies Elizabeth Scott Award, 1996^[3]
• First Emanuel and Carol Parzen Prize for Statistical Innovation, 1994

References

External links

• Grace Wahba at the Mathematics Genealogy Project
• Grace Wahba's University of Wisconsin website Home page
• Spline Models for Observational Data book