Dario Trevisan

Dario Trevisan is an Associate Professor at the University of Pisa, Italy. His research focuses on Optimal Transport, Probability Theory, Partial Differential Equations, and Geometric Analysis, with applications to Quantum Information Theory and Machine Learning. He has contributed significantly to the study of Wasserstein distances, stochastic processes, and geometric measure theory in metric measure spaces.

Key research interests include the asymptotic analysis of random matching problems, viscosity solutions in geometric spaces, and the interplay between functional inequalities and optimal transport. His work often bridges pure mathematics with applications in stochastic calculus and quantum mechanics.

He has organized several workshops and conferences, including the 2024 'Quantum Optimal Transport and Applications' and the 2023 'Calculus of Variations and Geometric Measure Theory.' His research has been published in leading journals such as Probability and Mathematical Physics and Journal of Functional Analysis.