My Journey

Education

• 2017 – 2021: Ph.D. in Computer Science and Systems Engineering at University of Genoa
• 2015 – 2021: M.Sc. in Computer Science (laude) at University of Genoa
• 2012 – 2015: B.Sc. in Computer Science (laude) at University of Genoa

Professional Experience

• 01/10/2025 – present: Tenure‑track Assistant Professor at University of Genoa
• 01/11/2022 – 30/09/2025: Fixed‑term Assistant Professor at University of Genoa
• 01/03/2022 – 14/05/2024: Collaborator – EU Project TESTABLE (Pluribus One S.r.l.)
• 18/01/2021 – 30/10/2022: Post‑doctoral Researcher – PRA Lab, Università di Cagliari
• 13/07/2016 – 12/09/2016: Internship – Miniclip Italia

Teaching Activities

• 2025 – 2027 Lecturer, Basi di Dati, Bachelor Degree in Computer Engineering (University of Genoa)

• 2022 – 2026 Co‑lecturer, Trustworthy Artificial Intelligence, Master Degree in Computer Engineering (University of Genoa)

• 2022 – 2026 Co‑lecturer, Sistemi Informativi, Bachelor Degree in Management Engineering (University of Genoa)

• 2022 – 2023 Co‑lecturer, Business Analytics, Master Degree in Management Engineering (University of Genoa)

• 2024 – 2025 Lecturer invited, Web‑based Informed Systems (University of Liechtenstein) Total hours: 6h

• 2024 – 2025 Invited lecturer, ML Security (University of Liechtenstein) Total hours: 3h

Ph.D. School and External Courses Participation

• 2026 – Security and Privacy in the Age of AI, KU Leuven
• 2026 – Adversarial Machine Learning, University of Genoa
• 2025 – Postgraduate Summer School II, Technical University of Madrid (UPM)
• 2025 – Adversarial Machine Learning, University of Genoa
• 2024 – Adversarial Machine Learning, University of Genoa
• 2023 – Adversarial Machine Learning, University of Genoa
• 2024 – Malware Detection in the AI Era: Attacks and Defenses on Machine Learning Classifiers, Black Hat 2024 (Las Vegas)
• 2023 – Summer School of Information Engineering (SSIE), University of Padua
• 2023 – Security and Privacy in the Age of AI, KU Leuven
• 2022 – Two Weeks International Winter School on Cyber‑security and Threat Intelligence, Cochin University of Science and Technology, online

Supervised Thesis

2026

• Luca Memori, Miglioramento del monitoraggio dei flussi informativi tra sistemi: mappatura casistiche e automatismi di supporto, B.Sc. in Ingegneria Gestionale, supervised by Silvia Papponetti (Leonardo S.P.A.)
• Ludovico Lozza, Impact of Adversarial EXEmples on Explainability Techniques for Malware Detection, M.Sc. in Computer Engineering

2025

• Bianca Perasso, Empirical Quantification of Spurious Correlations in Malware Detection, M.Sc. in Computer Engineering, co‑supervised with Prof. Roli
• Francesco Barberis, Extending evaluation metrics of COMPL‑AI, B.Sc. in Management Engineering, co‑supervised with Prof. Roli
• Lorenzo Bignardi, Use of LLMs in the Public Administration: Problems, Constraints, and Solutions, B.Sc. in Management Engineering, co‑supervised with Prof. Roli
• Francesca Scarrà, Certification of Videosurvaillance Systems, B.Sc. in Management Engineering, co‑supervised with Prof. Roli
• Ludovica Schilhan, AIBom: Improving model cards with Safety‑critical Information, B.Sc. in Management Engineering, co‑supervised with Prof. Roli

2024

• Cristian Casagrande, Improving the robustness evaluation of Machine Learning Windows malware detectors, B.Sc. in Computer Science
• Luca Pastore, AI cyber‑range for realistic testing of AI‑powered malware detectors, M.Sc. in Computer Engineering, co‑supervised with Prof. Roli
• Davide Luperini, AI Bill of Materials: towards a complete description of machine learning models, B.Sc. in Management Engineering (ongoing), supervised by Prof. Roli

2023

• Martina Battaglia, Next‑Generation Cyber Ranges for AI Security Evaluation: The Use Case of Malware Detection, M.Sc. in Computer Engineering, supervised by Prof. Roli
• Federico Simonelli, Automation of Security Testing for MLOps with Lightning AI, B.Sc. in Management Engineering, supervised by Prof. Roli
• Paola Grotti, Monitoring Security Testing Results through TensorBoard, B.Sc. in Management Engineering, supervised by Prof. Roli

2021

• Daniele Angioni, Robust Machine Learning for Malware Detection under Concept Drift, M.Sc. in Electronic Engineering, supervised by Prof. Battista Biggio and Dr. Maura Pintor
• Giovanni Manca, Understanding Failures of Gradient‑based Attacks on Machine Learning, M.Sc. in Computer Engineering, Cybersecurity and Artificial Intelligence, supervised by Prof. Battista Biggio and Dr. Maura Pintor
• Giorgio Piras, On Explainability of Machine Learning DGA detectors from DNS traffic data, M.Sc. in Computer Engineering, Cybersecurity and Artificial Intelligence, supervised by Prof. Battista Biggio and Dr. Maura Pintor

2019

• Giacomo Benedetti, Application of Adversarial Machine Learning to Malware Detection, B.Sc. in Computer Science, supervised by Prof. Giovanni Lagorio
• “Explaining Vulnerability of Deep Learning to Adversarial Windows Malware”, Italian Conference on Cyber‑Security (ITASEC), Italia

Public Presentations

2025

• Pick Two: Robustness, Accuracy, Real Correlations in Malware Detection with AI, invited talk at 4th Workshop on Rethinking Malware Analysis (WoRMA)
• Malware Detection with AI Systems: bridging the gap between industry and academia, invited talk at 4th International Workshop on Designing and Measuring Security in Systems with AI (DEMESSI)

2024

• Pentesting Windows Malware Detectors with Adversarial EXEmples. Invited by the research group “INRIA PIRAT” within the workshop “DefMal”, Rennes (FR)

2023

• Adversarial EXEmples: Functionality‑preserving Optimization of Adversarial Windows Malware. Invited by the research group “INRIA PIRAT” to the cycle of online seminars organized by them
• GPT‑like Pre‑Training on Unlabeled System Logs for Malware Detection TROOPERS DE

2021

• Adversarial EXEmples: Functionality‑preserving Optimization of Adversarial Windows Malware, Machine Learning and Data Mining (MLDM), AIxIA Workshop
• Adversarial EXEmples: Functionality‑preserving Optimization of Adversarial Windows Malware, 1st Huawei Innovation Workshop on Artificial Intelligence for Cyber‑Security, Huawei AI4Sec, online
• Adversarial EXEmples: Functionality‑preserving Optimization of Adversarial Windows Malware, Alan Turing Institute seminar series, online
• Formalizing evasion attacks against machine learning Windows malware detectors, Ciclo di seminari organizzato dal S3AI Group, online

2020

• Efficient black‑box optimization of adversarial windows malware with constrained manipulations, Avast CyberSec&AI, online
• WAF‑A‑MoLE: Evading Web Application Firewalls through Adversarial Machine Learning, Symposium of Applied Computing (SAC), online

2019

• Explaining Vulnerability of Deep Learning to Adversarial Windows Malware, Italian Conference on Cyber‑Security (ITASEC), Italy