Nick Polson is a Professor of Econometrics and Statistics at the Booth School of Business, University of Chicago. He graduated from Worcester College, Oxford University, and received his M.A. (Hons). Then, he received his Ph.D. at the University of Nottingham. Before his current role, he was a Lecturer at Nottingham University (1987–1989) and a Visiting Assistant Professor at Carnegie Mellon University (1989–1991). His research interests include Bayes, MCMC, Machine Learning, Deep Learning, Particle Learning, and Financial Econometrics.

Fabrizio Ruggeri received a B.Sc. degree in Mathematics from the University of Milano, Italy, in 1982, an M.Sc. degree in Statistics from Carnegie Mellon University, Pittsburgh, PA, USA, in 1989, and a Ph.D. degree in Statistics from Duke University, Durham, NC, USA, in 1994. He is currently a Senior Fellow at the Italian National Research Council, Milano, Italy, where he has been working since 1987. His research interests are mostly in Bayesian and industrial statistics, especially in robustness, decision analysis, reliability, and stochastic processes. Dr. Ruggeri is an ASA, IMS, and ISBA Fellow, an ISI Elected Member, an ENBIS Honorary Member, a former ISBA, ENBIS, and ISBIS President, and the current ISI President-Elect. He is a recipient of the Zellner Medal by ISBA. He has been Editor-in-Chief of the Applied Stochastic Models in Business and Industry journal for 17 years and Encyclopedia of Statistics in Quality and Reliability (Wiley, 2007), and he is still an Editor-in-Chief of Wiley StatsRef Online.

Vadim Sokolov obtained a Diploma (summa cum laude) in Applied Mathematics at Rostov State University and a Ph.D. in Computational Mathematics at Northern Illinois University. He currently works as an Associate Professor at the George Mason University. Before joining Mason, he was a Principal Computational Scientist at Argonne National Laboratory, a Fellow at the Computation Institute at the University of Chicago, and a Lecturer at the University of Chicago. He works on building robust solutions for large-scale complex systems analysis at the interface of simulation-based modeling and statistics. This involves developing new methodologies that rely on agent-based modeling, Bayesian analysis of time series data, design of computational experiments, and development of open-source software that implements those methodologies. Inspired by an interest in urban systems, he co-developed a mobility simulator called "Polaris" which is currently used for large-scale transportation network analysis by both local and federal governments.