Human-Explainable, Robust, and COllaborative LEarning.
At the HERCOLE Lab, our research mission is to advance the development of next-generation machine learning and artificial intelligence systems that are not only powerful, but also understandable, resilient, and decentralized.
We strive to make AI systems more interpretable and transparent to human users, enabling greater trust and collaboration. We design algorithms that are robust to adversarial attacks, ensuring reliability in real-world conditions.
Moreover, we design intelligent systems that can operate efficiently on edge devices, enabling local decision-making, enhancing privacy, and reducing reliance on centralized infrastructures.
Through interdisciplinary research and innovation, we aim to shape AI that is more human-centered, secure, and scalable.
We connect two key properties of machine learning models, generalization and explainability.
We introduce a multidisciplinary forum dedicated to using generative and agentic models to create faithful, robust, and human-centered Explainable AI narratives.
At ECIR 2026, we presented a position paper that rethinks recommender systems through the lens of empowerment, agency, and human flourishing.
