The American Public Health Association (APHA) has named Daniela Witten, a professor in statistics and biostatistics at the University of Washington and the Dorothy Gilford Endowed Chair in Mathematical Statistics, the winner of the 2019 Mortimer Spiegelman Award. This award honors a statistician who has made outstanding contributions to statistical methodology and its applications in public health.
“It is an honor to receive this award in recognition of my research in statistical machine learning, as well as my collaborative work,” Witten said. “As data sets continue to grow in size, and as the questions that researchers ask about these data become increasingly complex, there is an increasing need for the development of new statistical methods. This award highlights the importance of statistical machine learning to public health and other fields.”
Witten’s work focuses on statistical learning from complex, high-dimensional data. Her methodological work is motivated by collaborations in a number of fields, including genomics, neuroscience, microbial ecology, and pathology.
Rob Tibshirani, a professor of biomedical data science and statistics at Stanford University who has collaborated with Witten said, “Daniela is a rare researcher with the creativity to invent new statistical tools, and the scientific sense to know how and when to apply them in a way that can impact public health.”
“Dr. Witten is a star in statistical machine learning, the field of statistics that deals with developing models to make sense of complex and noisy data,” said Patrick Heagerty, University of Washington professor of statistics and biostatistics, and Gilbert S. Omenn Endowed Chair in Biostatistics.
“While statistical machine learning has a number of applications across many fields, Dr. Witten’s application areas are drawn primarily from biology,” continued Heagerty. “She has developed methods to accurately model transcriptional regulatory networks from complex noisy data without making unrealistic modeling assumptions; to identify the times at which neurons spike from noisy fluorescence traces measured using calcium imaging data; to model and perform downstream analyses of RNA sequencing data; to characterize the extent to which functionally-related genomic elements co-localize in the nucleus; and to learn the functional connectivity among a set of neurons.
“Her work requires a solid grounding in statistical modeling; a deep background of convex optimization; and an understanding of and enthusiasm for important biological problems. We are proud of her accomplishments and delighted that she received this well-deserved recognition for her scientific leadership.”
The Spiegelman Award has been presented annually since 1970 to a statistician under age 40 who has made outstanding contributions to public health statistics.
The Award serves to honor the outstanding achievements of the recipient, to encourage further involvement of the finest young statisticians in public health, and to increase awareness of APHA and the Applied Public Health Statistics Section in the academic statistical community.
Witten is invited to present her research at this year’s APHA conference, to be held November 2-6, where she will be presented with the award by last year’s recipient. She will also serve on the Spiegelman Award committee for the next three years, and will organize a session at the APHA annual meetings in 2020.