The Mathematics Department at the University of Puerto Rico is proud to inform the election of Dr. Luis Raúl Pericchi as one of the members (Class of 2026) of the Academy of Sciences of Latin America (ACAL) 
, for his contributions to statistics, Bayesian statistics, computational statistics and its applications. Congratulations Professor Pericchi!
The following excerpt is taken from the International Statistical Review:
“Luis Raúl Pericchi Guerra completed a B.S. in Mathematics in 1975 at the Universidad Simón Bolívar in Caracas, an M.S. in Statistics at the University of California Berkeley in 1978 and a Ph.D. in Statistics at Imperial College London in 1981. After graduating from Imperial College, Luis Raúl went back to Universidad Simón Bolívar. There, he played a key role in the developing of graduate programmes in Statistics and single handedly built an internationally recognised group focused on Bayesian statistics. In 2001, he moved to the Universidad de Puerto Rico in Rio Piedras to become the Chair of the Mathematics Department. At Universidad de Puerto Rico, he was instrumental in the establishment of a Ph.D. track in Computational Mathematics and Statistics. Luis Raúl has published over 120 papers in statistical and domain-specific journals, making significant contributions to several areas of Bayesian statistics (especially in the areas of model selection and Bayesian robustness) and their application (especially in hydrology). He is a Fellow of the American Statistical Association, the International Society for Bayesian Analysis, the John Simon Guggenheim Memorial Foundation and an Elected Member of the International Statistical Institute.”
Professor Pericchi has been instrumental in the creation and development of our Ph.D. program. He has been advisor or coadvisor of the following UPR Ph.D. graduates:
| Jean Keveny Innocent (2016) | Bayes factors consistency for nested linear models with increasing dimensions |
| Ang Li (2016) | Bayesian Calibration of $p$-values under Multiple Comparisons: Bounds and New Approximations |
| Kai Guo (2019) | Objective Bayesian Hypothesis Testing in Multivariate Situations |
| Daiver De Jesús Vélez Ramos (2019) | Calibrating significance level and $p$-values in linear models |
| Richard Clare (2023) | A universal robust bound for the intrinsic Bayes factor |