Jeffrey Blume

Quantitative Foundation Associate Dean of Academic and Faculty Affairs

The University of Virginia School of Data Science announces the appointment of Jeffrey D. Blume as the Quantitative Foundation Associate Dean of Academic and Faculty Affairs, effective July 25.

Blume is currently a tenured Professor of Biostatistics, with secondary appointments in Biomedical Informatics and Biochemistry at Vanderbilt University. He serves as Director of Graduate Education at Vanderbilt’s Data Science Institute and Vice-Chair of Education in the Department of Biostatistics. He is a leading expert in likelihood methods for measuring statistical inference, prediction modeling, and statistical methods for clinical trials. He recently proposed the ‘second-generation’ p-value: an improved tool for statistical inference that is easier to use and interpret and that has better error rate control and lower false discovery rates.

Blume brings to the School of Data Science (SDS) a proven track record of academic leadership and influential research and impactful collaborations in radiology, cancer diagnosis and prediction, nephrology, translational biomedicine, fMRI, and women’s health. He was recently elected a fellow of the American Statistical Association, awarded the Spinoza Chair in Medicine by the University of Amsterdam in 2019, and won multiple awards for teaching, mentoring, and research.

At Vanderbilt, Blume established a Ph.D. program in Biostatistics and served as Director of Graduate Studies for over 10 years. In 2018, he proposed and established an M.S. in Data Science, which was offered in their Data Science Institute, and welcomed their first class the following year. Prior to Vanderbilt, Blume spent eight years at Brown University where he served as Deputy Director of the Biostatistics and Data Management Center for the NCI-funded American College of Radiology Imaging Network. While at Brown, he helped launch their Master of Public Health program and helped design clinical trials evaluating new medical imaging technology.

Blume’s methodologic research is extensive. He is widely published on topics such as evidential philosophy of statistical inference, likelihood methods, second-generation p-values, prediction modeling, mediation modeling, ROC curves, sequential testing, trial design, empirical Bayes methods for biomedical data, false discovery rates, model selection, and neuroimaging. He has a broad and extensive track record of impactful collaborative work from designing national clinical trials on diagnostic imaging techniques to revising national lung cancer screening guidelines to reduce racial disparities.

Committed to using data science for the common good, Blume was a senior author on a widely publicized paper that proposed revised lung cancer screening guidelines to reduce racial disparities, earning him Vanderbilt’s Chancellor Award for Research Equity, Diversity, and Inclusion.

Blume holds a Ph.D. in Biostatistics from Johns Hopkins University and a B.A. in Statistics from the State University of New York at Buffalo.