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I am a member of the PADS and AnaNSi research groups of the University of Bologna and I work on parallel and distributed systems. My work is organized in three lines, which often overlap. The full list of my scientific articles is in the publications page.
Parallel and distributed simulation
I study how to run large simulations on multiple processors and networked computers, from multicore and GPUs to the cloud: adaptive middleware, model partitioning, fault tolerance. More recently I work on multilevel modeling and on using simulation to study complex networks, the Internet of Things and blockchains.
Selected works:
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GEMMA: a meta-model for multilevel modeling and simulation.
[doi]
[paper]
Software and Systems Modeling, 2026.
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A Review of Multilevel Modeling and Simulation for Human Mobility and Behavior.
[doi]
[paper]
Simulation Modelling Practice and Theory, 2023.
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The Simulation Model Partitioning Problem: an Adaptive Solution Based on Self-Clustering.
[doi]
[paper]
Simulation Modelling Practice and Theory, 2017.
Security and privacy
I work on protecting data and services in distributed systems: protocols that guarantee transaction confidentiality while preserving verifiability, privacy in crowdsensing and location-based services, secure sharing of health data, software reproducibility. With Giampiero Giacomello I wrote a book for a general audience on cybersecurity (in Italian).
Selected works:
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An auditable confidentiality protocol for blockchain transactions.
[doi]
[paper]
Blockchain: Research and Applications, 2026.
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Understanding Build Reproducibility in the F-Droid Ecosystem.
[doi]
[paper]
ACM REP 2026.
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Cybersicurezza: che cos'è e come funziona.
[info]
Book (in Italian) with Giampiero Giacomello, il Mulino, 2023.
Blockchain and cryptocurrencies
I study blockchains and cryptocurrencies: I analyze transaction networks with complex network theory and machine learning (also to detect illicit activity) and design decentralized services for data management, smart mobility and healthcare.
Selected works:
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Enhancing Anti-Money Laundering Frameworks: An Application of Graph Neural Networks in Cryptocurrency Transaction Classification.
[doi]
[paper]
IEEE Access, 2025.
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On the Ethereum blockchain structure: A complex networks theory perspective.
[doi]
[paper]
Concurrency and Computation: Practice and Experience, 2020.
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A Framework Based on Distributed Ledger Technologies for Data Management and Services in Intelligent Transportation Systems.
[doi]
[paper]
IEEE Access, 2020.
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