News
09/2026: Honoured to receive a Bronze Teaching Award from the University of Oxford, Department of Engineering Science.
08/2026: Delighted to receive a research grant from Amazon Robotics for our project on learning-enhanced control of large-scale multi-robot systems with closed-loop guarantees.
07/2026: Our invited session on System Level Synthesis and the tutorial paper Learning, Adapting, and Certifying Control Policies in System-Level Coordinates were accepted for the 66th IEEE Conference on Decision and Control. The tutorial paper and session website will be added soon.
07/2026: Technical presentation at ECC 2026, in the workshop Control Theory: Yesterday's News or Tomorrow's Foundation?
06/2026: Invited talk at the SIAM Conference on Optimization: Learning to Optimize: Guarantees from Convex to Non-Convex Landscapes.
04/2026: Three papers accepted at the IFAC World Congress 2026.
04/2026: New preprint: Learning Over-Relaxation Policies for ADMM with Convergence Guarantees, by Junan Lin, Paul J. Goulart, and Luca Furieri.
03/2026: New preprint: Stability-Preserving Online Adaptation of Neural Closed-loop Maps, by Danilo Saccani, Luca Furieri, and Giancarlo Ferrari-Trecate.
03/2026: New preprint: Safety-Aware Performance Boosting for Constrained Nonlinear Systems, by Danilo Saccani, Haoming Shen, Luca Furieri, and Giancarlo Ferrari-Trecate.
01/2026: New preprint: Characterizing All Locally Exponentially Stabilizing Controllers as a Linear Feedback Plus Learnable Nonlinear Youla Dynamics, by Luca Furieri.
12/2025: New preprint: Distributed Control of Network Systems in the Space of Stabilizing Graph Neural Network Policies, by John Cao and Luca Furieri.
11/2025: New preprint: A Graph-Informed Regret Metric for Optimal Distributed Control, by Daniele Martinelli, Andrea Martin, Giancarlo Ferrari-Trecate, and Luca Furieri.
08/2025: New preprint: Learning to Optimize with Guarantees: A Complete Characterization of Linearly Convergent Algorithms, by Andrea Martin, Ian R. Manchester, and Luca Furieri.