It is easy (and accurate) to say that Grace Wahba is this country's most eminent female statistician, but it is also misleading: Grace is in the top few among all American statisticians, and is in fact one of our most important applied mathematicians. She was also the first female faculty member in the Department of Statistics at UW–Madison. Supervising the theses of 39 graduate students from four continents, her career there lasted 51 years, ending with retirement in August 2018.
Grace almost owns the word “spline” as it is used in statistics; her 1990 monograph Spline Models for Observational Data has been a scientific best-seller. It is based on a series of fundamental papers written with various co-authors in the preceding years. Of these, the most influential might be 1979's “Generalized cross-validation as a method of choosing a good ridge parameter”, with Gene Golub and Michael Heath, which introduced the GCV (generalized cross validation) criterion. The hallmark of Grace Wahba's work is a combination of high-powered mathematics, often involving functional analysis ideas such as reproducing kernel Hilbert spaces, but with the practical problems of real data analyses kept firmly in view. The very best statisticians always turn out to be good scientists as well as good mathematicians, and Grace certainly fits that description.