Pietro Liò

My research interest focuses on developing Artificial Intelligence and Computational Biology models to understand diseases complexity and address personalised and precision medicine. Current focus is on Graph Neural Network modeling to build predictive models based on the integration of multi scale, multi omics and multi physics data; integrate deep learning and mechanistic approaches; explainability and interpretability in medicine; exploiting short and long range communications in the human body, between cells and tissues and predict emerging mechanistic properties at systemic medicine level. Develop an AI-based medical digital twin to increase self-awareness; Develop an AI personal decision support system to increase social awareness.

Taghizad, N. and Lio, P., 2025 (Published online). A Systematic Review on the Integrating Artificial Intelligence for Enhanced Fault Detection in Power Transmission Systems: A Smart Grid Approach Computing&AI Connect, v. 2 Doi: 10.69709/caic.2024.103229 Purificato, A., Cassarà, G., Siciliano, F., Liò, P. and Silvestri, F., 2025 (Published online). Sheaf4Rec: Sheaf Neural Networks for Graph-based Recommender Systems ACM Transactions on Recommender Systems, Doi: 10.1145/3742898 Singh, V., Khanzadeh, M., Davis, V., Rush, H., Rossi, E., Shrader, J. and Lio’, P., 2025 (Published online). Bayesian Binary Search Algorithms, v. 18 Doi: 10.3390/a18080452 Ali, R., Caso, F., Irwin, C. and Liò, P. , 2025. Entropy-Lens: The Information Signature of Transformer Computations. CoRR, v. abs/2502.16