Join me for PhD at the University of Oxford
(click for fully-funded scholarship)



Are you passionate about the intersection of control systems and machine learning?
I am looking for talented PhD candidates to join me in October 2025.

Research projects

Scalable design of networked control systems

In this project, you will develop new optimization- and AI-based frameworks to control LARGE-scale dynamical systems, addressing stability and robustness challenges when multiple agents interact with conflicting goals and information, as seen in energy networks and traffic systems.

  • Key topics: Graph Neural Networks (GNNs), safe Reinforcement Learning (RL), convex optimization
  • Relevant publications: [P1-1], [P1-2], [P1-3]

    • Learning to optimize with convergence and generalization guarantees

    In this project, you will explore how ML techniques can improve the performance of optimization algorithms in tasks requiring convergence guarantees. Key applications include nonlinear model predictive control, federated learning, high-complexity physics simulations, and generative adversarial networks.

    • Key topics: meta-optimization, nonlinear optimization and control, statistical learning theory
    • Relevant publications: [P2-1], [P2-2], [P2-3]

    Application process

    Contact me for an informal inquiry and discussion of your interests at luca.furieri@epfl.ch.
    In your email, please briefly motivate your fit within one of the above projects, and include the following documents:

    • CV      
    • Transcripts     
    • Sample of your work (thesis, research paper)     
    • Contact of 2 references     

    Important: excellent candidates will be invited to submit a full application to the Department of Engineering Sciences. Details are available on the course page of the University website.

    Deadline: 3rd December, 2024

    Some additional funding sources offered by Oxford University include: