Pellungrini Roberto
Born and raised in Viareggio, Tuscany, Roberto Pellungrini is a PhD student in Computer Science at the University of Pisa. His main research interests concern ethical aspects related to Data Science, in particular regarding Privacy issues. Before winning the PhD scholarship, he attained a Master Degree in Business Informatics with a thesis on Assessing Privacy Risk and Quality in Human Mobility Data
- Position
- Research Fellow
- Affiliation
- Scuola Normale Superiore
Projects
Publications
2024
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, “Enhancing Privacy and Utility in Federated Learning: A Hybrid P2P and Server-Based Approach with Differential Privacy Protection”, in Proceedings of the 21st International Conference on Security and Cryptography - SECRYPT, 2024.
2023
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, “EXPHLOT: EXplainable Privacy assessment for Human LOcation Trajectories”, in Discovery Science , 2023.
2020
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, “Predicting and Explaining Privacy Risk Exposure in Mobility Data”, in Discovery Science, Cham, 2020.
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, “Prediction and Explanation of Privacy Risk on Mobility Data with Neural Networks”, in ECML PKDD 2020 Workshops, Cham, 2020.
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, “Modeling Adversarial Behavior Against Mobility Data Privacy”, IEEE Transactions on Intelligent Transportation SystemsIEEE Transactions on Intelligent Transportation Systems, pp. 1 - 14, 2020.
2019
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, “Human Mobility from theory to practice: Data, Models and Applications”, in Companion of The 2019 World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019., 2019.
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, “Privacy Risk for Individual Basket Patterns”, in ECML PKDD 2018 Workshops, Cham, 2019.
2018
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, “Analyzing Privacy Risk in Human Mobility Data”, in Software Technologies: Applications and Foundations - STAF 2018 Collocated Workshops, Toulouse, France, June 25-29, 2018, Revised Selected Papers, 2018.
2017
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, “Assessing Privacy Risk in Retail Data”, in Personal Analytics and Privacy. An Individual and Collective Perspective - First International Workshop, PAP 2017, Held in Conjunction with ECML PKDD 2017, Skopje, Macedonia, September 18, 2017, Revised Selected Papers, 2017.
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, “A Data Mining Approach to Assess Privacy Risk in Human Mobility Data”, ACM Trans. Intell. Syst. Technol., vol. 9, pp. 31:1–31:27, 2017.
Pages
Blog
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