I am originally from Colombia.
I do research in Bayesian statistics from a theoretical and practical view point.
J. Fúquene-Patiño, M. Steel and D, Rosell. On choosing mixture components via non-local priors (2019). 81, 5, 809-837. Journal of the Royal Statistical Society, Series B .
J. Fúquene-Patiño and Brenda Betancourt and João B. M. Pereira (2018). A weakly informative prior for Bayesian dynamic model selection with applications in fMRI. Journal of Applied Statistics 45 (7), 1173-1192.
J. Fúquene-Patiño, M. E. Perez, and L. R. Pericchi (2014). An alternative to the Inverted Gamma for the variances to modelling outliers and structural breaks in dynamic models Brazilian Journal Of Probability and Statistics. Vol. 28, No. 2, 288–299.
J. Fúquene-Patiño, J. D. Cook and L.R. Pericchi (2009) A Case for Robust Bayesian Priors with Applications to Clinical Trials, pp. 817 - 846, Bayesian Analysis.
J. Fúquene-Patiño (2015) A Semi-parametric Bayesian Extreme Value Model using a Dirichlet Process Mixture of Gamma densities. Journal of Applied Statistics, Volume 42, Number 2, 1 February 2015, pp. 267-280 (14).