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 through logic-based approaches that deliver transparent explanations. I apply XAI methods for scientific discovery, particularly in drug design, and I'm passionate about creating interpretable reinforcement learning agents that provide transparent decision-making processes.

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Alessio Ragno

Featured Publications

On Logic-based Self-Explainable Graph Neural Networks

Ragno, A.; Plantevit, M.; Robardet, C.
NeurIPS 2025

CIP-Net: Continual Interpretable Prototype-based Network

Di Valerio, F.; Proietti, M.; Ragno, A.; Capobianco, R.
AAAI 2026 (Association for the Advancement of Artificial Intelligence)

Prototype-based Interpretable Graph Neural Networks

Ragno, A.; La Rosa, B.; Capobianco, R.
IEEE Transactions on Artificial Intelligence, 2022

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