Daniela Witten, a University of Washington professor of statistics and biostatistics, has been named a 2018 Simons Investigator in Mathematical Modeling of Living Systems by the Simons Foundation’s Division of Mathematics and Physical Sciences and Division of Life Sciences. The program awards $100,000 per year over a five-year period to outstanding scientists like Witten for use in furthering their research. Additional funds are provided to UW and the Department of Biostatistics for a total award of $660,000.
The honor recognizes Witten’s work, which focuses on “the development of supervised and unsupervised learning methods for making sense of large and messy data sets arising from genomics, neuroscience and other fields.” Witten has developed new frameworks for performing clustering, graphical modeling and matrix decompositions in the high-dimensional setting.
“In recent years, technology development in biology has outpaced the development of statistical methods to make sense of the data resulting from this new technology,” says Witten. "My research aims to bridge this gap."
DNA sequencing, fMRI, calcium imaging, and other biomedical technologies result in a huge number of measurements; however, due to the cost of these technologies, the number of observations for which these measurements are collected is relatively small. In this “high-dimensional” setting, classical statistical techniques (which require a very large number of observations) cannot be applied. Witten’s work focuses on developing statistical methods that can disentangle signal from noise in this challenging setting.
“It is a huge honor for my work to be recognized by the Simons Foundation,” says Witten. “I am delighted to have an opportunity to pursue research at the interface of statistical machine learning and biology, and to become part of the diverse and vibrant community of Simons Investigators."
Witten is one of sixteen theoretical scientists named 2018 Simons Investigators in the fields of Mathematics, Physics, Computer Science and Mathematical Modeling of Living Systems. The program is designed to support scientists in the early stages of an academic career when they are establishing creative new research directions, providing leadership to the field and effectively mentoring junior scientists.
About Daniela Witten
Daniela Witten is a professor of statistics and biostatistics at University of Washington.
Her research involves the development of statistical machine learning methods for high-dimensional data, with applications to genomics, neuroscience, and other fields. She is particularly interested in unsupervised learning, with a focus on graphical modeling.
Witten is the recipient of a number of honors, including a NDSEG Research Fellowship, 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. Her work has been featured in the popular media; among other forums, in Forbes Magazine (three times) and Elle Magazine, on KUOW radio (Seattle's local NPR affiliate station), in a NOVA documentary, and as a PopTech Science Fellow.
She co-authored (with Gareth James, Trevor Hastie, and Rob Tibshirani) the popular textbook “Introduction to Statistical Learning". She was a member of the Institute of Medicine committee that released the report “Evolution of Translational Omics".
Witten completed a BS in Math and Biology with Honors and Distinction at Stanford University in 2005, and a PhD in Statistics at Stanford University in 2010.