marastoni
univr
it
Niccolò Marastoni’s research interests include software security, program analysis, and machine learning techniques for code understanding. His work has focused on malware analysis, program similarity, and the application of deep learning methods to the classification of programs.
More recently, his research has investigated how LLM-driven approaches can complement traditional static and dynamic analysis methods to improve the effectiveness of vulnerability detection.
He has also contributed to the area of recommender systems, exploring data mining techniques such as association rule learning and the Apriori algorithm to extract meaningful patterns from data and support recommendation tasks.
Niccolò Marastoni is a researcher and Temporary Assistant Professor at the University of Verona, where he has been involved in research projects spanning software security, data mining, and machine learning, and has authored publications in international conferences and journals in these areas.
Modules running in the period selected: 5.
Click on the module to see the timetable and course details.
| Course | Name | Total credits | Online | Teacher credits | Modules offered by this teacher |
|---|---|---|---|---|---|
| Master's degree in Data Science | Programming and database (2025/2026) | 12 |
|
6 | (Programming) |
| Master's degree in Data Science | Programming and database (2024/2025) | 12 |
|
6 | (Programming) |
|
Master's degree in Data Science
Course partially running
|
Programming and database (2023/2024) | 12 |
|
6 | (Programming) |
|
Master's degree in Data Science
Course partially running
|
Programming and database (2022/2023) | 12 |
|
6 | (Programming) |
|
Master's degree in Data Science
Course partially running
|
Programming and database (2021/2022) | 12 |
|
6 | (Programming) |
Di seguito sono elencati gli eventi e gli insegnamenti di Terza Missione collegati al docente:
| Topic | Description | Research area |
|---|---|---|
| Context and Ethics Aware Data Integration and Management | In the era of big data and semantically rich information, integrating data from diverse sources while customizing it for high-quality, context-aware applications, such as recommender systems, has become essential. This approach ensures that these applications meet functional requirements and align with ethical standards and user expectations. |
Information Systems and Data Analytics
Data management systems |
| Software and application security | Development of security methodologies and technologies for the security of software systems and Internet applications |
Cybersecurity
Software and application security |
| Title | Starting date |
|---|---|
| DataGEMS | 10/25/24 |
| NEUROPULS - NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS | 1/1/23 |
| Title | Starting date |
|---|---|
| DataGEMS | 10/25/24 |
| NEUROPULS - NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS | 1/1/23 |
| Office | Collegial Body |
|---|---|
| Member | Mathematics and Data Science Teaching Committee - Department Computer Science |
| Member | Computer Science Department Council - Department Computer Science |
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