PhD Candidate

SYSCOP Laboratory

University of Freiburg

Andrea Ghezzi was born in Bergamo, Italy, in 1996. He obtained his Master degree cum laude in Automation and Control Engineering from Politecnico di Milano with a thesis about stochastic MPC with constraint prioritization. From December 2020 to September 2021 he was a researcher at Data Science R&D Department of Tenaris, in Dalmine, Italy, working on virtual sensing for improving the steelmaking process. From October 2021 he joined SYSCOP Laboratory at University of Freiburg, carrying out a PhD under the supervision of Prof. Dr. Moritz Diehl. He is a Marie-Curie fellow of the ELO-X project.

Project description

Andrea works mainly on algorithms for solving mixed-integer nonlinear problems (MINLPs), with a focus on problems arising from the transcription of optimal control problems via direct methods.  Besides, he is interested in nonlinear model predictive control and its deployment on embedded hardware.



Ghezzi, Andrea; Hoffman, Jasper; Frey, Jonathan; Boedecker, Joschka; Diehl, Moritz

Imitation Learning from Nonlinear MPC via the Exact Q-Loss and its Gauss-Newton Approximation Proceedings Article Forthcoming

In: 2023 Conference on Decision and Control (CDC), Forthcoming.

Abstract | Links | BibTeX


Ghezzi, Andrea; Simpson, Léo; Bürger, Adrian; Zeile, Clemens; Sager, Sebastian; Diehl, Moritz

A Voronoi-Based Mixed-Integer Gauss-Newton Algorithm for MINLP Arising in Optimal Control Proceedings Article

In: 2023 European Control Conference (ECC), pp. 1-7, IEEE, Bucharest, Romania, 2023, ISBN: 978-3-907144-08-4.

Abstract | Links | BibTeX


Ghezzi, Andrea; Messerer, Florian; Balocco, Jacopo; Manzoni, Vincenzo; Diehl, Moritz

An Implicit and Explicit Dual Model Predictive Control Formulation for a Steel Recycling Process Journal Article

In: European Journal of Control, pp. 100841, 2023, ISSN: 0947-3580.

Abstract | Links | BibTeX


Simpson, Léo; Ghezzi, Andrea; Asprion, Jonas; Diehl, Moritz

An Efficient Method for the Joint Estimation of System Parameters and Noise Covariances for Linear Time-Variant Systems Proceedings Article Forthcoming

In: 2023 Conference of Decision and Control (CDC) , Forthcoming.

Abstract | Links | BibTeX