Statistical Modelling

The research line in Statistical Modelling focuses on developing, evaluating, and applying statistical techniques to analyze and interpret complex data. This field explores various methodologies such as regression analysis, Bayesian inference, time series, and generalized linear models, survival analysis, aiming to make sense of high-dimensional, non-linear, and often noisy data. Research often focuses on improving the robustness, efficiency, and interpretability of models for diverse applications, from predictive modeling in healthcare and environmental sciences to decision-making in economics and business.