Daniela Witten, professor of biostatistics and statistics at University of Washington and the Dorothy Gilford Endowed Chair in Mathematical Statistics, has received the prestigious 2022 Presidents’ Award from the Committee of Presidents of Statistical Societies (COPSS).
The COPSS Presidents' Award is the highest honor in the field of statistics, and is given annually to a statistician under the age of 41 in recognition of their outstanding contributions to the field.
"I’m immensely grateful to the statistical community for this recognition, and for this career that is so fulfilling scientifically, professionally, and personally," said Witten.
The Presidents’ award citation states that Witten was selected “for bridging the gap between the questions that scientists are asking about their data and the statistical methods that are available to provide insightful answers, especially in the context of biomedical research; for developing flexible and interpretable approaches for modeling large-scale and high-dimensional data; and for the significant elevation of statistical science via successful translation of statistical ideas to a broad audience.”
Witten's award was announced at the recent Joint Statistical Meetings (JSM). The five societies that sponsor the award include the American Statistical Association (ASA), the Statistical Society of Canada (SSC), the Institute of Mathematical Statistics (IMS), the Eastern North American Region of the International Biometric Society (ENAR), and the Western North American Region of the International Biometric Society (WNAR).
Daniela Witten is a professor of statistics and biostatistics at University of Washington, and the Dorothy Gilford Endowed Chair in Mathematical Statistics. She develops statistical machine learning methods for high-dimensional data, with a focus on unsupervised learning. Daniela is the recipient of an NIH Director’s Early Independence Award, a Sloan Research Fellowship, an NSF CAREER Award, a Simons Investigator Award in Mathematical Modeling of Living Systems, and the Mortimer Spiegelman Award. She is also a co-author of the popular textbook Introduction to Statistical Learning.
