Dario Azzimonti is a Lecturer and Researcher at the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI), part of the Department of Innovative Technologies (DTI) at SUPSI, in Lugano, Switzerland. His research sits at the intersection of probabilistic machine learning, uncertainty quantification, and time series forecasting, with a particular focus on Gaussian processes and their applications to real-world predictive modeling problems. He received his PhD in 2016 and subsequently held a postdoctoral position at the Idiap Research Institute in Martigny, Switzerland, before joining IDSIA. His academic work spans both theoretical and applied dimensions, including contributions to Bayesian optimization, preference learning, probabilistic forecasting, and hierarchical forecast reconciliation, with results published in peer-reviewed journals and conferences across statistics, machine learning, and forecasting. His work is funded by Innosuisse, the Swiss National Science Foundation (SNSF), and European research programs, in collaboration with both academic institutions and industry partners.