Wilson is currently working on developing algorithms for approximating complex distributions. A key application of his work is in Bayesian inference. He also develops forecasting models for financial time series.
Recently, Chief investigator Wand and his has group published Kim & Wand (2016, Electronic Journal of Statistics), Wand (2017, Journal of American Statistical Association) and Nolan & Wand (2017, Stat) on message passing approaches to semiparametric regression analysis.
Prizes, awards and special recognition
ACEMS Sampling and Exploration Competition, 2017 RESEARCH FELLOWCATEGORY, SECOND PLACE was awarded to Wilson Chen. Awarded from the ACEMS.