Lorenzo obtained his Ph.D. in Computer Science at UC Berkeley. His research focuses on the theoretical study of algorithms, with the goal to design methods that are both mathematically sound and applicable in practice. Lorenzo’s research has produced algorithmic advances for foundational computational problems, both of combinatorial nature, such as graph clustering, and of continuous nature, such as the solution of systems of linear equations and of large resource-allocation linear programs. He advocates a broad approach to the design of algorithm that incorporates techniques from discrete and continuous optimization and is able to model computational challenges arising in a variety of applications, including Machine Learning, Numerical Analysis and Combinatorial Optimization.