Daniela Witten
Daniela Witten, Ph.D., is Professor of Statistics and Biostatistics at the University of Washington, where she holds the Dorothy Gilford Endowed Chair in Mathematical Statistics.
Professor Witten develops statistical machine learning methods for high-dimensional data, with a focus on unsupervised learning.
She is the recipient of an NIH Director’s Early Independence Award, a Sloan Research Fellowship, an NSF CAREER Award, and a Simons Investigator Award in Mathematical Modeling of Living Systems. She received the Presidents’ Award from the Committee of Presidents of Statistical Societies (COPSS), awarded annually to a statistician under age 41 in recognition of outstanding contributions to the field of statistics.
Witten also received the Spiegelman Award from the American Public Health Association for a statistician under age 40 who has made outstanding contributions to statistics for public health, and the Leo Breiman Award for contributions to the field of statistical machine learning. She is a Fellow of the American Statistical Association and the Institute for Mathematical Statistics, and an Elected Member of the International Statistical Institute.
She is a co-author of the very popular textbook Introduction to Statistical Learning. She has served as an Associate Editor for Biometrika, the Journal of Computational and Graphical Statistics, and the Journal of the American Statistical Association, and as an Action Editor for Journal of Machine Learning Research. Since 2023, she has served as Joint Editor of the Journal of the Royal Statistical Society, Series B.
You can visit her university webpage here.
You can visit her personal webpage here.