Curriculum vitæ

Employment

Assistant professor (RTD-A), Department of Computer Science, University of Pisa (since May 5th, 2025)
Post-doc research fellow, Department of Computer Science, University of Pisa, with a grant from the Future AI Research (FAIR) project (February 1st, 2024 – May 4th, 2025)

Education

Ph.D. in Computer Science cum laude, University of Pisa, 2024
- Thesis “Efficient Models for Deep Learning on Graphs” under the supervision of prof. Alessio Micheli
M.Sc. in Computer Science cum laude, University of Pisa, 2020
B.Sc. in Computer Engineering cum laude, University of Salerno, 2017

Conference organization

31st International Conference on Artificial Neural Networks (ICANN 2022), Program Committee member ↪
32nd International Conference on Artificial Neural Networks (ICANN 2023), Program Committee member ↪
Temporal Graph Learning Workshop @ NeurIPS 2023, Program Committee member ↪
2nd International Workshop on Reservoir Computing @ ICANN 2024, Organizing Committee ↪
14th IAPR-TC15 International Workshop on Graph-Based Representations in Pattern Recognition (GbR 2025), Program Committee member ↪
Special Session on Design and Theory of Deep Graph Learning @ IJCNN 2025, Organizing Committee ↪
3rd International Workshop on Reservoir Computing @ ICANN 2025, Organizing Committee ↪
Special Session on Neural Networks for Graphs and Beyond (NN4G+) @ ICANN 2025, Organizing Committee ↪
2026 IEEE World Congress on Computational Intelligence / International Joint Conference on Neural Networks (IJCNN 2026), Area Chair
35th International Conference on Artificial Neural Networks (ICANN 2026), Publication Chair ↪
Special Session on Neural Networks for Graphs and Beyond (NN4G+) @ ICANN 2026, Organizing Committee ↪
4th International Workshop on Reservoir Computing @ ICANN 2026, Organizing Committee ↪

Editorship

Intelligenza Artificiale, the official journal of the Italian Association for Artificial Intelligence (AIxIA), Editorial Board member ↪

Service and leadership

Secretary of the European Neural Network Society (since 2026)
Vice-Chair of the IEEE Student Branch of Pisa (2023-2024)
Institute of Electrical and Electronics Engineers (IEEE), member since 2016
Association for Computing Machinery (ACM), member since 2017
European Neural Network Society (ENNS), member since 2022
CVPL, the Italian chapter of the International Association for Pattern Recognition (IAPR), member since 2024

Awards

Best paper award at GbRPR 2023 for Minimum Spanning Set Selection in Graph Kernels
PhD thesis award - Premio di studio per tesi di dottorato di ricerca 2025 - Settore 1 – “Scienze Matematiche e Informatiche, Scienze Fisiche, Scienze della Terra”
PhD thesis award con.Scienze (2025 edition) for the best Computer Science PhD thesis, awarded by the National Conference of Presidents and Directors of University Departments in Science and Technology.
Best paper award at the 4th International Workshop on Deep Learning meets Neuromorphic Hardware (DLMNH 2026) for Randomized Ising Models for Network Quantification: Novel Applications for Unconventional Computing.

Publications

Re-evaluating Out-of-Distribution Learning in Drug Discovery

F. Capria, A. Micheli, D. Tortorella (2027). "Re-evaluating Out-of-Distribution Learning in Drug Discovery." AIxIA 2026 – Advances in Artificial Intelligence. AIxIA 2026, LNCS vol. 17131, pp. 143-154.

Graph Learning Models for Temporal Gene Expression Prediction and the Role of Interactions Topology

A. Dipalma, A. Micheli, P. Milazzo, F. Simonetti, D. Tortorella (2027). "Graph Learning Models for Temporal Gene Expression Prediction and the Role of Interactions Topology." Computational Methods in Systems Biology. CMSB 2026, LNCS vol. 16678, pp. 334-350.

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.

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.

Investigating Time-Scales in Deep Echo State Networks for Natural Language Processing

C. Baccheschi, A. Bondielli, A. Lenci, A. Micheli, L. Passaro, M. Podda, D. Tortorella (2025). "Investigating Time-Scales in Deep Echo State Networks for Natural Language Processing." Artificial Neural Networks and Machine Learning. ICANN 2025 International Workshops and Special Sessions, LNCS vol. 16072, pp. 188-200.

An Empirical Investigation of Shortcuts in Graph Learning

D. Tortorella, M. Fontanesi, A. Micheli, M. Podda (2025). "An Empirical Investigation of Shortcuts in Graph Learning." Graph-Based Representations in Pattern Recognition. GbRPR 2025. LNCS vol. 15727, pp. 147-156.

An Empirical Evaluation of Rewiring Approaches in Graph Neural Networks

A. Micheli, D. Tortorella (2025). "An Empirical Evaluation of Rewiring Approaches in Graph Neural Networks." Pattern Recognition Letters, vol. 196, pp. 134–141.

Robustness in Protein-Protein Interaction Networks: A Link Prediction Approach

A. Dipalma, D. Tortorella, A. Micheli (2025). "Robustness in Protein-Protein Interaction Networks: A Link Prediction Approach." Proceedings of the 33rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2025), pp. 277-282.

Encoding Graph Topology with Randomized Ising Models

D. Tortorella, A. Brau, A. Micheli (2025). "Encoding Graph Topology with Randomized Ising Models." Proceedings of the 33rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2025), pp. 271-276.

Analyzing Explanations of Deep Graph Networks through Node Centrality and Connectivity

M. Fontanesi, A. Micheli, M. Podda, D. Tortorella (2025). "Analyzing Explanations of Deep Graph Networks through Node Centrality and Connectivity." Proceedings of the 27th International Conference on Discovery Science (DS 2024), LNCS vol. 15243, pp. 295-309.

Continual Learning with Graph Reservoirs: Preliminary experiments in graph classification

D. Tortorella, A. Micheli (2024). "Continual Learning with Graph Reservoirs: Preliminary experiments in graph classification." Proceedings of the 32nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2024), pp. 35-40.

Onion Echo State Networks: A Preliminary Analysis of Dynamics

D. Tortorella, A. Micheli (2024). "Onion Echo State Networks: A Preliminary Analysis of Dynamics." Proceedings of the 33rd International Conference on Artificial Neural Networks (ICANN 2024), LNCS vol. 15025, pp. 117-128.

Continuously Deep Recurrent Neural Networks

A. Ceni, P. F. Dominey, C. Gallicchio, A. Micheli, L. Pedrelli, D. Tortorella (2024). "Continuously Deep Recurrent Neural Networks." Machine Learning and Knowledge Discovery in Databases: Research Track. ECML PKDD 2024. LNCS vol. 14947, pp. 59-73.

Designs of Graph Echo State Networks for Node Classification

A. Micheli, D. Tortorella (2024). "Designs of Graph Echo State Networks for Node Classification." Neurocomputing, vol. 597, 127965.

Entropy Based Regularization Improves Performance in the Forward-Forward Algorithm

M. Pardi, D. Tortorella, A. Micheli (2023). "Entropy Based Regularization Improves Performance in the Forward-Forward Algorithm." Proceedings of the 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2023), pp. 393-398.

Domenico Tortorella, PhD