I am Stefano Sarao Mannelli, a tunure-track Assistant Professor in the Data Science and AI division in the Computer Science department of Chalmers University of Technology and Gothenburg University. Prior to my current position, I worked as a postdoc with Andrew Saxe at the University College London and the University of Oxford and obtained a Ph.D. in Physics applied to Machine Learning at the University of Paris-Saclay supervised by Lenka Zdeborova. My research focuses on analysing machine learning problems using a model-based approach, where the complexity of the problem is reduced to obtain a parsimonious solvable model that still captures the phenomenon of interest. In my previous works, I applied several variations of this approach to study problems in learning, such as transfer learning, continual learning, and curriculum learning.