Bayesian Statistics Award Winners—Dr. Abhra Sarkar, Kelly Kang, and Tianjian Zhou

Please join SDS in congratulating Dr. Abhra Sarkar, Kelly Kang, and Dr. Tianjian Zhou for receiving the following prestigious awards for their work in Bayesian Statistics.

Dr. Abhra Sarkar, Assistant Professor

Abhra Sarkar was the lead author of the paper awarded the prestigious Mitchell Prize that is given annually by ISBA/SBSS “in recognition of an outstanding paper that describes how a Bayesian analysis has solved an important applied problem.” Dr. Sarkar's winning paper is titled “Bayesian Semiparametric Mixed Effects Markov Models With Application to Vocalization Syntax” and appeared in JASA in 2018.

The Mitchell Prize is a significant honor and a testament to Dr. Sarkar's growing reputation as a leader in statistical neuroscience. The paper introduces a new statistical modeling framework that can be used to better understand the neurological, genetic, and evolutionary basis of human vocal communication mechanisms using animal vocalization models.  

Kelly Kang, SDS PhD Candidate

Kelly Kang, (advised by Dr. Stephen Walker), was one of the Section of Bayesian Statistical Science (SBSS) student paper award winners this year.  Kelly's award winning paper is titled, "A new class of unimodal, asymmetric, heavy-tailed densities with applications to regression and time-series models."

PhD Alumnus Tianjian Zhou

Dr. Tianjian Zhou, (advised by Dr. Peter Mueller), received an honorable mention (2nd place) for the Savage Award in the Applied Methodology category, given for the top dissertations in Bayesian statistics. Dr. Zhou thus follows in the footsteps of Drs. Carlos Carvalho and James Scott, who both were recognized in the Savage Award competition when they were starting out their careers.