I’m a PhD student at Queen Mary University of London under the supervision of Paulo Rauber. My research focuses on developing reinforcement learning algorithms that are both scalable and sample-efficient, with a particular emphasis on Bayesian and model-based approaches. In addition to my academic work, I am also a research scientist at xDNA, where I develop both Natural Language Processing and Computer Vision applications.

 Curriculum Vitae


  • R. Sasso, M. Conserva, P. Rauber.
    “Posterior Sampling for Deep Reinforcement Learning”
    International Conference on Machine Learning (ICML), 2023.
  • R. Sasso, M. Sabatelli, Marco Wiering.
    “Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning”
    Transactions on Machine Learning Research (TMLR), 2023.