About Me

I am a postdoc at the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano, where I work with Prof. Alberto Marchesi. I received my PhD in computer science at Politecnico di Milano, where I was advised by Prof. Nicola Gatti. During my PhD, I had the opportunity to be a visiting researcher at the Industrial Engineering & Operations Research (IEOR) Department at Columbia University, where I was fortunate to work with Prof. Christian Kroer. My current research focuses on the theoretical aspects of artificial intelligence and online learning. In particular, I am interested in combining online (machine) learning theoretical tools with optimization techniques to build strategic agents able to act in complex online environments.

More details in my CV.

Contacts:
Email: francescoemanuele DOT stradi AT polimi.it

Publications

Conference Papers
  • Truly Adapting to Adversarial Constraints in Constrained MABs [COLT 2026]
    Francesco Emanuele Stradi, Kalana Kalupahana, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
    The 39th Annual Conference on Learning Theory, COLT 2026, San Diego, USA
  • No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! [NeurIPS 2025]
    Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti, Christian Kroer
    The 39th Conference on Neural Information Processing Systems, NeurIPS 2025, San Diego, USA
  • Data-Dependent Regret Bounds for Constrained MABs [NeurIPS 2025]
    Gianmarco Genalti*, Francesco Emanuele Stradi*, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
    The 39th Conference on Neural Information Processing Systems, NeurIPS 2025, San Diego, USA
  • Taming Adversarial Constraints in CMDPs [NeurIPS 2025]
    Francesco Emanuele Stradi, Anna Lunghi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
    The 39th Conference on Neural Information Processing Systems, NeurIPS 2025, San Diego, USA
  • Markov Persuasion Processes: Learning to Persuade From Scratch [NeurIPS 2025]
    Francesco Bacchiocchi*, Francesco Emanuele Stradi*, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
    The 39th Conference on Neural Information Processing Systems, NeurIPS 2025, San Diego, USA
  • Learning Adversarial MDPs with Stochastic Hard Constraints [ICML 2025]
    Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
    The 42nd International Conference on Machine Learning, ICML 2025, Vancouver, Canada
  • Policy Optimization for CMDPs with Bandit Feedback: Learning Stochastic and Adversarial Constraints [ICML 2025]
    Francesco Emanuele Stradi, Anna Lunghi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
    The 42nd International Conference on Machine Learning, ICML 2025, Vancouver, Canada
  • Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization [ICLR 2025]
    Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
    The 13th International Conference on Learning Representations, ICLR 2025, Singapore, Singapore
  • Bandits with Ranking Feedback [NeurIPS 2024]
    Davide Maran*, Francesco Bacchiocchi*, Francesco Emanuele Stradi*, Matteo Castiglioni, Nicola Gatti, Marcello Restelli
    The 38th Conference on Neural Information Processing Systems, NeurIPS 2024, Vancouver, Canada
  • Online Learning in CMDPs: Handling Stochastic and Adversarial Constraints [ICML 2024]
    Francesco Emanuele Stradi, Jacopo Germano, Gianmarco Genalti, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
    The 41st International Conference on Machine Learning, ICML 2024, Vienna, Austria
  • Online Learning with Off-Policy Feedback in Adversarial MDPs [IJCAI 2024]
    Francesco Bacchiocchi*, Francesco Emanuele Stradi*, Matteo Papini, Alberto Maria Metelli, Nicola Gatti
    The 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024, Jeju Island, South Korea
  • Online Markov Decision Processes Configuration with Continuous Decision Space [AAAI 2024]
    Davide Maran*, Pierriccardo Olivieri*, Francesco Emanuele Stradi*, Giuseppe Urso, Nicola Gatti, Marcello Restelli
    The 38th AAAI Conference on Artificial Intelligence, AAAI 2024, Vancouver, Canada
    PhD Thesis
  • Regret Minimization in Constrained Markov Decision Processes [Thesis]
    External Reviewers: Prof. Haipeng Luo, Matteo Pirotta, PhD.

    • Teaching

  • Probabilità e Statistica Matematica
    B.Sc. in Management Engineering
    TA during the academic years 2023-2024
  • Statistica
    B.Sc. in Mechanical Engineering
    TA during the academic years 2023-2024