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).

Research topics

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

Upcoming conferences

• 35th International Conference on Artificial Neural Networks (ICANN 2026) ↪
• Special Session on Neural Networks for Graphs and Beyond (NN4G+) @ ICANN 2026 ↪
• 4th International Workshop on Reservoir Computing @ ICANN 2026 ↪

Recent publications

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, in press.

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.

Bridging XAI and spectral analysis to investigate the inductive biases of deep graph networks

M. Fontanesi, A. Micheli, M. Podda, D. Tortorella (2025). "Bridging XAI and spectral analysis to investigate the inductive biases of deep graph networks." Machine Learning, vol. 114, 257.

Contact

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