Grace Goldsmith Wahba (born August 3, 1934) is an American statistician and retired I. J. Schoenberg-Hilldale Professor of Statistics at the University of Wisconsin–Madison.[1] She is a pioneer in methods for smoothing noisy data. Best known for the development of generalized cross-validation[2] and "Wahba's problem",[1] she has developed methods with applications in demographic studies, machine learning, DNA microarrays, risk modeling, medical imaging, and climate prediction.
Biography
Wahba had an interest in science from an early age, when she was in junior high she was given a chemistry set.[3] At this time she was also interested in becoming an engineer.[3]
Wahba studied at Cornell University for her undergraduate degree.[3] When she was there women were severely restricted in their privileges, for example she was required to live in a dorm and had a curfew.[3] She received her bachelor's degree from Cornell University in 1956 and a master's degree from the University of Maryland, College Park in 1962.[1] She worked in industry for several years before receiving her doctorate from Stanford University in 1966 and settling in Madison in 1967.
She is the author of Spline Models for Observational Data.[4] She retired in August 2018 from the University of Wisconsin-Madison.[3] Her life and career are discussed in a 2020 interview.[5]
Honors and awards
Wahba was elected to the American Academy of Arts and Sciences in 1997[6] and to the National Academy of Sciences in 2000.[7] She is also a fellow of several academic societies including the American Association for the Advancement of Science, the American Statistical Association, and the Institute of Mathematical Statistics.[8]
Over the years she has received a selection of notable awards in the statistics community:
R. A. Fisher Lectureship, COPSS, August 2014[9]
Gottfried E. Noether Senior Researcher Award, Joint Statistics Meetings, August 2009
Committee of Presidents of Statistical Societies Elizabeth Scott Award, 1996[9]
First Emanuel and Carol Parzen Prize for Statistical Innovation, 1994
She received honorary Doctor of Science degrees from the University of Chicago in 2007 and The Ohio State University in 2022.
The Institute of Mathematical Statistics announced the IMS Grace Wahba Award and Lecture in 2021.[10]
References
"Breaking ground with Grace". news.wisc.edu. Retrieved 2018-11-16.
Craven, Peter; Wahba, Grace (1978-12-01). "Smoothing noisy data with spline functions". Numerische Mathematik. 31 (4): 377–403. doi:10.1007/BF01404567. ISSN 0945-3245. S2CID 14094416.
"Grace Goldsmith Wahba | Department of Statistics". statistics.stanford.edu. Retrieved 2019-10-06.
Wahba, G. (1990-01-01). Spline Models for Observational Data. CBMS-NSF Regional Conference Series in Applied Mathematics. Society for Industrial and Applied Mathematics. doi:10.1137/1.9781611970128. ISBN 9780898712445.
Douglas Nychka, Ping Ma, and Douglas Bates (2020). "A Conversation with Grace Wahba". Statistical Science. 35 (2): 308–320. doi:10.1214/19-STS734.
"Grace Wahba". American Academy of Arts and Sciences. Retrieved 24 June 2021.
"National Academy of Sciences". Retrieved 22 February 2016.
"Grace Wahba: Honors". Retrieved 22 February 2016.
"Institute of Mathematical Statistics". Archived from the original on 12 March 2016. Retrieved 22 February 2016.
"ims-grace-wahba-award-and-lecture". 27 May 2021. Retrieved 24 June 2021.
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