Daniele Corradini is a PhD candidate at the Institute of Geophysics and Meteorology, University of Cologne, Germany. He received an M.Sc. in Applied Physics and an M.Sc. in Physics of the Earth System from the University of Bologna, Italy, where he specialized in complex systems, biomedical data analysis, atmospheric physics, and remote sensing. During his studies, he completed an internship at Tampere University, Finland, where he worked on the simulation of spiking neural networks. He subsequently joined the Biophysics Group at the Department of Physics and Astronomy, University of Bologna, as a Research Fellow, conducting research on artificial intelligence for medical imaging and machine learning methods for the analysis of electrical activity in neural populations. His current research focuses on the application of artificial intelligence to precipitation retrievals and earth observation, with particular emphasis on self-supervised learning, satellite remote sensing of clouds and severe convection, and the evaluation of numerical weather prediction and climate models using geostationary satellite observations with a focus on extreme events over complex terrain. His broader research interests include explainable AI, representation learning, and the application of data-driven methods to atmospheric sciences.