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

• ICANN 2022, Program Committee member ↪
• ICANN 2023, Program Committee member ↪
• Temporal Graph Learning Workshop @ NeurIPS 2023, Program Committee member ↪
• 2nd International Workshop on Reservoir Computing @ ICANN 2024, Organizing Committee member ↪
• 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 member ↪
• 3rd International Workshop on Reservoir Computing @ ICANN 2025, Organizing Committee member ↪
• Special Session on Neural Networks for Graphs and Beyond (NN4G+) @ ICANN 2025, Organizing Committee member ↪

Service and leadership

• 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

Publications

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.

Richness of Node Embeddings in Graph Echo State Networks

D. Tortorella, A. Micheli (2023). "Richness of Node Embeddings in Graph Echo State Networks." Proceedings of the 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2023), pp. 11-16.

Minimum Spanning Set Selection in Graph Kernels

D. Tortorella, A. Micheli (2023). "Minimum Spanning Set Selection in Graph Kernels." Graph-Based Representations in Pattern Recognition. GbRPR 2023. LNCS vol. 14121, pp. 15-24.

Addressing Heterophily in Node Classification with Graph Echo State Networks

A. Micheli, D. Tortorella (2023). "Addressing Heterophily in Node Classification with Graph Echo State Networks." Neurocomputing, vol. 550, 126506.

Leave Graphs Alone: Addressing Over-Squashing without Rewiring

D. Tortorella, A. Micheli (2022). "Leave Graphs Alone: Addressing Over-Squashing without Rewiring" (Extended Abstract). Presented at the First Learning on Graphs Conference (LoG 2022), Virtual Event, December 9–12, 2022.

Beyond Homophily with Graph Echo State Networks

D. Tortorella, A. Micheli (2022). "Beyond Homophily with Graph Echo State Networks." Proceedings of the 30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2022), pp. 491-496.

Hierarchical Dynamics in Deep Echo State Networks

D. Tortorella, C. Gallicchio, A. Micheli (2022). "Hierarchical Dynamics in Deep Echo State Networks." Proceedings of the 31st International Conference on Artificial Neural Networks (ICANN 2022), pp. 668-679.

Spectral Bounds for Graph Echo State Network Stability

D. Tortorella, C. Gallicchio, A. Micheli (2022). "Spectral Bounds for Graph Echo State Network Stability." Proceedings of the 2022 International Joint Conference on Neural Networks.

Discrete-Time Dynamic Graph Echo State Networks

A. Micheli, D. Tortorella (2022). "Discrete-Time Dynamic Graph Echo State Networks." Neurocomputing, vol. 496, pp. 85-95.

Dynamic Graph Echo State Networks

D. Tortorella, A. Micheli (2021). "Dynamic Graph Echo State Networks." Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2021), pp. 99-104.

Talks

Conference Proceeding talk 3 on Relevant Topic in Your Field

March 01, 2014

Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA

Talk 2 on Relevant Topic in Your Field

February 01, 2014

Talk at London School of Testing, London, UK

Tutorial 1 on Relevant Topic in Your Field

March 01, 2013

Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA

Talk 1 on Relevant Topic in Your Field

March 01, 2012

Talk at UC San Francisco, Department of Testing, San Francisco, California

Teaching

TA for the Machine Learning course (fall 2024)

TA for the Machine Learning course (fall 2022)