Statistics doctoral candidate Giorgio Paulon has been selected as one of ten winners of the American Statistical Association Section of Bayesian Statistical Science (SBSS) Student Paper Competition. Giorgio will be considered for SBSS’s top prize for student papers – the Laplace Award – which will be announced at the Joint Statistical Meetings (JSM) in August.
Giorgio's paper, “Bayesian Semiparametric Longitudinal Drift-Diffusion Mixed Models for Tone Learning in Adults," has recently been accepted for publication in the Journal of the American Statistical Association, Application and Case Studies (link). The article introduces a new class of Bayesian semiparametric drift-diffusion mixed models for multi-alternative decision making in longitudinal settings. In particular, the model mimics tone learning’s neural mechanisms and it allows us to understand how adult humans learn nonnative speech categories such as tone information.
The article was written in collaboration with auditory neuroscientists Fernando Llanos (the University of Texas at Austin) and professor Bharath Chandrasekaran (University of Pittsburgh). He will present its contents at the (JSM) 2021 this summer.
Giorgio is advised by Abhra Sarkar.
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.
