Alessio Ragno
Associate Professor (Enseignant-Chercheur) at EPITA
I conduct research in Explainable Artificial Intelligence and Scientific Discovery at EPITA's Research Laboratory (LRE). My work focuses on developing self-explainable models, with a particular emphasis on Graph Neural Networks, Drug Discovery, and Reinforcement Learning. Beyond interpretability for its own sake, I'm passionate about leveraging XAI as a tool to guide and accelerate scientific discovery turning model explanations into actionable insights for real-world applications.
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Featured Publications
CIP-Net: Continual Interpretable Prototype-based Network
AAAI 2026 (Association for the Advancement of Artificial Intelligence)
Prototype-based Interpretable Graph Neural Networks
IEEE Transactions on Artificial Intelligence, 2022