Predicting individual and collective human behavior is crucial to address complex societal challenges. Recent research has focused on deep learning models for forecasting future behavior. While these models achieve impressive results, they face limitations:

limited generalizability, low interpretability, and difficulties in geographic transfer. This PhD project aims to design the next generation of computational models for understanding individual and collective human behavior. Social science research on social learning,

collective intelligence, and crowd wisdom identifies potentially generalizable behavioral patterns. Additionally, recent advancements in AI offer foundation models capable of reasoning and generalization.

The ideal candidate possesses a strong interest in a multidisciplinary approach encompassing machine learning (deep learning and foundation models), social sciences, urban mobility, and related fields. The ultimate goal is to contribute to the development of the first foundation model for human behavior.

The collaborative nature of the project fosters engagement with leading national and international universities, creating a dynamic research environment.