Domenico Tortorella received the PhD in computer science cum laude from the University of Pisa, Italy, in 2024 for his thesis “Efficient Models for Deep Learning on Graphs” under the supervision of prof. Alessio Micheli. Previously he received the BSc in computer engineering from the University of Salerno, Italy, in 2017, and the MSc in computer science from the University of Pisa, Italy, in 2020, both cum laude. Currently, he is an assistant professor (RTD-A) in the Department of Computer Science at the University of Pisa, and he is a member of the Computational Intelligence and Machine Learning research group (CIML). He currently hold the office of Secretary of the European Neural Network Society (ENNS).

Research topics

• Machine learning for graphs
• Reservoir computing
• Constructive neural networks

Upcoming conferences

• 15th IAPR-TC15 International Workshop Graph-Based Representations in Pattern Recognition (GbR 2027) ↪

Recent publications

A method for the systematic generation of graph XAI benchmarks via Weisfeiler–Leman coloring

M. Fontanesi, A. Micheli, M. Podda, D. Tortorella (2026). "A method for the systematic generation of graph XAI benchmarks via Weisfeiler–Leman coloring." Data Mining and Knowledge Discovery, vol. 40(4), 42.

Randomized Ising models for graph node representation

M.G. Berni, A. Brau, A. Micheli, D. Tortorella (2026). "Randomized Ising models for graph node representation." Neurocomputing, vol. 679, 133195.

Efficient quantification on large-scale networks

A. Micheli, A. Moreo, M. Podda, F. Sebastiani, W. Simoni, D. Tortorella (2025). "Efficient quantification on large-scale networks." Machine Learning, vol. 114, 270.

Contact

Room 330
Department of Computer Science, University of Pisa
Largo B. Pontecorvo, 3, 56127 Pisa, Italy