Bárbara González, Ph.D.

Associate Professor

Bárbara González has published research in Bayesian statistics, stochastic processes, random variable generation, visualization techniques, mathematics education and leadership.

She specializes in the development of rigorous Bayesian methodologies and the analysis of complex stochastic systems. Her research at the intersection of Bayesian inference and extreme value theory has fundamentally advanced the understanding of tail probability estimation, providing critical insights into the divergence between Bayesian and frequentist paradigms when modeling rare events. Beyond foundational theory, González develops sophisticated model-selection frameworks for hierarchical data, including linear mixed-effects models. Her work in stochastic processes has been instrumental in characterizing Internet traffic dynamics, packet-arrival mechanisms, and the performance of network flow control. As an interdisciplinary scholar, González applies her expertise to critical challenges in healthcare—such as autism care—and financial systems, while remaining dedicated to pedagogical innovation in the mathematical sciences. Her research has appeared in Queueing Systems, Journal of Applied Probability, the New England Journal of Statistics in Data Science, Sankhya B, and Statistics & Probability Letters.

Education

Ph.D., Cornell University — Bayesian Statistics and Stochastic Processes

Selected Publications

B. González-Arévalo and A. Rodríguez (2025): A New Method to Generate Uniform Random Variates on the Unit Spherical Shell in R^d, Journal of Simulation.

B. González-Arévalo (2025): Faculty Affairs in research intensive universities: Supporting Faculty Success at Northern Illinois University. In Zeineldin, R. A practitioner's guide to faculty affairs. Routledge. Case study.

N. Shen, B. González-Arévalo and L.R. Pericchi (2023): Comparison Between Bayesian and Frequentist Tail Probability Estimates, The New England Journal of Statistics in Data Science, 1(2), 208-215, https://doi.org/10.51387/23-NEJSDS39.