Sandra Fortini

Dr. Sandra Fortini is Associate Professor of Statistics in the Department of Decision Sciences at Bocconi University. With research spanning Bayesian statistics, machine learning, and nonparametric models, she investigates asymptotic properties of statistical procedures and predictive inference frameworks. Her methodological work has applications in biostatistics, neural network theory, and clinical trial design.

Core research domains include:

• Asymptotic behavior of Bayesian and machine learning algorithms
• Deep neural network theory and infinite-width limits
• Exchangeability principles in predictive modeling
• Non-asymptotic approximations in statistical learning
• Bayesian nonparametric methods

Recent publications demonstrate strong focus on neural network theory (60% of 2023-2024 works) and Bayesian clinical trial methodologies (40%). Her 2024 Biostatistics article introduces innovative uncertainty-directed factorial designs, while 2023-2024 neural network publications establish fundamental limit theorems for deep learning architectures.

Significant recognitions include fellowship status in four prestigious societies: Institute of Mathematical Statistics, International Society for Bayesian Analysis, Italian Statistical Society, and Italian Mathematical Society. Teaching responsibilities encompass probability theory and stochastic processes for undergraduate and graduate programs at Bocconi.