Hello, I'm
Giulia
Pedrielli
Associate Professor • Arizona State University
Black-Box Methods for Complex Engineered Systems
I am an Associate Professor in the School of Computing & Augmented Intelligence at Arizona State University, where I have been on faculty since 2016. My research focuses on the theory and application of black-box and gray-box optimization, with a particular emphasis on surrogate-based, Bayesian, and simulation-based methods for complex engineered systems.
Before joining ASU, I was a postdoctoral fellow at the National University of Singapore (Industrial Engineering) and at Politecnico di Milano & the Italian National Research Council (CNR). I hold a PhD in Mechanical Engineering from Politecnico di Milano, and spent part of my doctoral training as a visiting researcher at UC Berkeley (IEOR).
My work bridges operations research, machine learning, and simulation — developing algorithms for problems where analytical solutions are unavailable: digital twins, cyber-physical systems, biomanufacturing, RNA design, and critical infrastructure resilience.
Research Interests
- Black-Box & Bayesian Optimization
- Gray-Box & Simulation-Based Optimization
- Digital Twins & Cyber-Physical Systems
- Stochastic & Global Optimization
- Computational Biology (RNA Design)
- Biomanufacturing & Smart Manufacturing
- Critical Infrastructure Resilience