Marco Mangano

Marco Mangano received his PhD in Aerospace Engineering from the University of Michigan. His graduate research focused on Multidisciplinary Design Analysis and Optimization (MDAO) for wings and turbine blades using CFD and FEM structural solvers.

He is now leveraging his experience in nonlinear PDE-constrained optimization to develop novel optimization algorithms for digital twins, with particular focus on optimal experimental design problems. His interests also include distributed optimization, multiphysics simulations, and energy and transportation system design.

He has already co-authored several journal and conference papers that appeared in Renewable Energy, JOSS, Scientific Reports, and multiple AIAA journals. His previous work on aerodynamic shape optimization has been recognized with the 2019 AIAA Applied Aerodynamics Best Paper award.

Research Interests:

• PDE-constrained optimization
• Digital twins, uncertainty quantification, and optimal experimental design
• Distributed optimization
• Large-scale Multidisciplinary Design Optimization