Gelly’s research interests lie in financial modelling and forecasting and her research uses among others Bayesian nonparametric and semiparametric framework, via Markov chain Monte Carlo, for the construction of quantile time series models for financial data. Prior to joining the Department of Statistics, Gelly spent four years at the University of Kent, where she completed a PhD in Actuarial Science at the School of Mathematics, Statistics, and Actuarial Science. Her PhD thesis was on the use of quantile methods to better estimate and forecast the time-varying conditional asset return.