2019 Statistics Department Dissertation Awards

With great appreciation for all those involved in the nomination and review process, we proudly announce this year’s doctoral dissertation award winners. Each hard-won distinction is accompanied by a prize of $1,000 and recipients will be presented with their certificates during the department's diploma ceremony on June 16th. Our warmest congratulations are offered to these outstanding PhD students!

♦ Theodore W. Anderson Theory of Statistics Dissertation Award to Pragya Sur for deep, original results in large sample maximum likelihood theory for logistic regression with a large numbers of covariates

♦ Jerome H. Friedman Applied Statistics Dissertation Award to Gene Katsevich for developing new methodology to identify simultaneously which genes and which DNA variants are important for traits of interest and proposing the use of a combination of  the lasso and knockoff framework, allowing researchers to focus more precisely on variants that might have a causal effects; and by coordinating the search across genes and polymorphisms it reduces false positives

♦ Ingram Olkin Interdisciplinary Research Dissertation Award to Alex Chin for contributions to the study of causal inference under interference, bringing to bear a diverse range of modern statistical approaches including importance sampling, regression adjustment, and Stein’s method to this important interdisciplinary problem