Marco Bagatella

PhD student in RL, currently at the Learning and Adaptive Systems group.

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bio

I am a PhD student at MPI-IS and ETH Zürich, co-advised by Georg Martius and Andreas Krause. Previously, I was fortunate to spend some time at Meta in Paris, working with Andrea Tirinzoni and Alessandro Lazaric, at the AIT Lab (ETH Zürich), under the supervision of Prof. Otmar Hilliges, and in the Autonomous Learning Group (MPI IS Tübingen). Not so long ago, I obtained a MSc in Computer Science at ETH Zürich, and a few years before that I graduated from Politecnico di Milano (BSc in Engineering of Computing Systems).

research

I am mainly interested in (deep) reinforcement learning, particularly in extracting diverse behavior from offline data and adapting it online. I am very excited about zero-shot methods, and the interplay between multi-task pre-training and test-time adaptation. Outside of RL, I have some experience in representation learning, and I like keeping an eye open towards recent developments with vision/language/action/… models.

news

Oct 15, 2025 🎉 DISCOVER was accepted at NeurIPS 2025.
Oct 01, 2025 ⛰️ I completed a wonderful internship at FAIR (Paris) and I am back in Zurich!
May 01, 2025 🎉 Active Fine-Tuning of Multi-task Policies and Zero-Shot Offline Imitation Learning via Optimal Transport were accepted at ICML 2025.
Aug 01, 2024 🎉 Directed Exploration in Reinforcement Learning from Linear Temporal Logic was accepted at EWRL 2024
Jul 22, 2024 🪧 Two papers I was involved in were presented at ICML 2024

selected publications

  1. tdjepa.png
    TD-JEPA: Latent-predictive Representations for Zero-Shot Reinforcement Learning
    Marco Bagatella, Matteo Pirotta, Ahmed Touati, and 2 more authors
    In arXiv, 2025
  2. optibfm.png
    Optimistic Task Inference for Behavior Foundation Models
    Thomas Rupf, Marco Bagatella, Marin Vlastelica Pogancic, and 1 more author
    In arXiv, 2025
  3. discover.png
    DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning
    Leander Diaz Bone, Marco Bagatella, Jonas Hübotter, and 1 more author
    In Advances in Neural Information Processing Systems, 2025
  4. amf.png
    Active Fine-Tuning of Generalist Policies
    Marco Bagatella, Jonas Hübotter, Georg Martius, and 1 more author
    In Forty-second International Conference on Machine Learning, 2025
  5. zilot.png
    Zero-shot Offline Imitation Learning via Optimal Transport
    Thomas Rupf, Marco Bagatella, Nico Gürtler, and 2 more authors
    In Forty-second International Conference on Machine Learning, 2025
  6. gcopfce.png
    Goal-conditioned Offline Planning from Curious Exploration
    Marco Bagatella, and Georg Martius
    In Advances in Neural Information Processing Systems, 2023