Jennifer Starling: SBSS award winner
Statistics doctoral candidate Jennifer Starling has been selected as one of ten Section of Bayesian Statistical Science (SBSS) student paper award winners for Joint Statistical Meetings 2020. Jennifer is advised by James Scott. Her paper is titled "BART with Targeted Smoothing: An analysis of patient-specific stillbirth risk" and is to appear in Annals of Applied Statistics.
The Section on Bayesian Statistical Science provides a platform for people interested in Bayesian statistics to converse and share their thoughts about the Bayesian paradigm. Some of the objectives of the SBSS are to encourage research on theories and methods that are associated with Bayes’ theorem. If you are interested in finding out more about Bayesian Statistical Science and the objectives and writing competitions that the SBSS holds, visit their website here.
This year there were sixty entrants for the SBSS student paper. Of these sixty people, ten had outstanding papers and were selected as winners. Of these ten students, nine will be awarded $800 travel awards and one will receive $1,200 travel award. All ten winners will be presented with a certificate at the SBSS section meeting in 2020.
Congratulations to Jennifer Starling, a University of Texas at Austin Ph.D. Candidate, for being one of the ten winners.
April 5, 2022 • by the Department of Statistics and Data Sciences
September 14, 2021 • by the Department of Statistics and Data Sciences
September 23, 2020 • by the Department of Statistics and Data Sciences