I am an Associate Professor of Engineering Science at the University of Oxford and a Tutorial Fellow at St Hugh's College.
My group works at the interface of control theory, optimization, and machine learning. We study how large-scale interconnected dynamical systems can be controlled, adapted, and optimized under structural, informational, and safety constraints, with a particular focus on distributed control, learning-enabled control with formal guarantees, and control-theoretic approaches to algorithm design.
Before joining Oxford, I was a Principal Investigator and postdoctoral researcher at EPFL. I received my PhD in 2020 from ETH Zurich (Automatic Control Laboratory, IfA). Recognitions of my work include the SNSF Ambizione career grant, the TCNS Best Paper Award, and the ACC O. Hugo Schuck Award.
Recent updates
- 11/2025 PhD applications for the DPhil in Engineering Science are open. Deadline: 2 December 2025, 12:00 (UK) for entry in October 2026. Contact me as soon as possible to discuss. Formal applications via the Oxford admissions page: DPhil in Engineering Science (Oxford).
- 09/2025 Our paper "Learning to optimize over linearly convergent algorithms: gotta characterize 'em all" (Andrea Martin, Ian R. Manchester, Luca Furieri) has been accepted for an oral presentation at the ScaleOPT workshop, NeurIPS 2025. Preprint: arXiv:2508.00775.
- 09/2025 Invited talk at the AI and Data Talk Series webinar of the ACE Network, on connections between neural network control and learning-based optimization. LinkedIn post.
- 08/2025 New preprint: Learning to optimize with guarantees: a complete characterization of linearly convergent algorithms (Andrea Martin, Ian R. Manchester, Luca Furieri).
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07/2025
CDC 2025:
- MAD: A Magnitude And Direction Policy Parametrization for Stability Constrained Reinforcement Learning accepted for presentation.
- Invited session on "Control Theory for Algorithm Analysis and Design", organized by Andrea Martin, Guido Carnevale, Nicola Bastianello, and myself.
- 06/2025 Invited talk at the ECC 2025 workshop "Systems Theory of Optimization, Learning, and Control Algorithms".
- 06/2025 Joined the University of Oxford as an Associate Professor of Engineering Science.
- 04/2025 New preprint: MAD: A Magnitude And Direction Policy Parametrization for Stability Constrained Reinforcement Learning .
- 02/2025 Visiting Prof. Yang Zheng and his group at UC San Diego; presented recent work on learning-based control and optimization. LinkedIn post.
- 09/2024 Paper On the guarantees of minimizing regret in receding horizon accepted in the IEEE Transactions on Automatic Control.
- 08/2024 Paper Learning to boost the performance of stable nonlinear systems accepted in the IEEE Open Journal of Control Systems.
- 06/2024
ECC 2024 in Stockholm:
- Organised the workshop Neural Networks in Control.
- Paper: Closing the gap to quadratic invariance: a regret minimization approach to optimal distributed control.
- Paper: Regret optimal control for uncertain stochastic systems (European Journal of Control).
- Paper: Unconstrained learning of networked nonlinear systems via free parametrization of stable interconnected operators.
- 06/2024 Invited talk at University of Stuttgart (Kolloquium Technische Kybernetik), hosted by Prof. Andrea Iannelli. Slides.
- 05/2024 Paper Learning to optimize with convergence guarantees using nonlinear system theory accepted.