Nicholas Polson is a Bayesian statistician who conducts research on Financial Econometrics, Markov chain Monte Carlo, Particle learning, and Bayesian inference. Inspired by an interest in probability, Polson has developed a number of new algorithms and applied them to the fields of statistics and financial econometrics, including the Bayesian analysis of stochastic volatility models and sequential particle learning for statistical inference. Polson’s article, “Bayesian Analysis of Stochastic Volatility Models,” was named one of the most...