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Mateus Maia Marques is a Research Associate focused on statistical machine learning models, with a strong emphasis on predictive tasks. His core research interests include Bayesian methodologies, ensemble methods, and advanced statistical learning models. Over the past few years, he has developed and extended statistical methodologies to suit various contexts and assumptions. This work is complemented by his efforts in creating and maintaining R packages, which are openly accessible to the community, thus facilitating broader use and collaboration. Currently, he is involved in the Project 4 Resilience initiative where he applies statistical methodologies, particularly extreme value theory and spatio-temporal models, to enhance energy forecasting. The project's aim is to improve the resilience of energy systems by providing accurate and reliable forecasts under varying conditions.