Our mission
The Collaborative AI Lab - CAIL at Bocconi comprises a multidisciplinary group of researchers conducting theoretical, algorithmic and applied studies on intelligent systems, building on tools from computer science, statistical physics, statistics, theoretical economics, and computational biology. Mathematics is their common language.
The research activities include algorithms, cognitive modelling, machine learning, computer vision, rational decision making and game theory, statistical learning and stochastic optimization.
CAIL is part of Bocconi University’s broader education and research initiative on AI, in collaboration with Fondazione Compagnia di San Paolo.
Research Activities
The research activities of the Lab include:
- machine learning, deep learning and representation learning;
- generative AI, reinforcement learning and foundation models;
- learning theory, statistical learning and stochastic optimization;
- algorithms, computational optimization and high-performance computing for AI;
- security, privacy and cryptography for AI systems and data collaboration;
- responsible, trustworthy and explainable AI;
- computational neuroscience, cognitive modelling and biologically inspired learning;
- computational biology, bioinformatics and biomedical AI;
- rational decision making, game theory and AI for economics and management;
- cross-industry AI applications, prototypes and applied research projects.