Alessandro Rudi

Alessandro Rudi is a Professor at Bocconi University's Department of Economics, Politics and Decision Sciences, specializing in Digital Transformation. His research bridges mathematical optimization and machine learning through kernel methods and polynomial decomposition techniques.

Recent publications reveal focus areas in mathematical programming, including global optimization via kernel approximations, smooth transport map estimation, and sum-of-squares hierarchies for trigonometric polynomials. His work demonstrates exponential convergence properties and functional decomposition approaches.

Key subfields include non-convex optimization, optimal transport theory, constrained mathematical modeling, and vector-valued regression frameworks. These studies connect broader disciplines of machine learning, computational mathematics, and statistical data science.