Filippo Sciarrone
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Filippo Sciarrone has a total of 63 co-authors. Here are the top co-authors by number of shared publications:
- Carla Limongelli
Roma Tre University
28 shared publications - Marco Temperini
Sapienza University of Rome
28 shared publications - Stefano D'URso
Universitas Mercatorum
10 shared publications Giulia Vaste
9 shared publicationsMarco Temperini
Sapienza University
7 shared publicationsAlessandro Marani
Compono Pty Ltd., Brisbane, QLD, Australia
6 shared publications
Latest Publications
- 2 July 2026
- Published by Springer Nature
- p. 67-82
DyslexIA: Empowering Dyslexic Students with Accessible Learning Through AI
- 2 July 2026
- Published by Springer Nature
- p. 67-82
DyslexIA: Empowering Dyslexic Students with Accessible Learning Through AI
- 2 July 2026
- Published by Springer Nature
- p. 83-95
Criterium: Assisting Teachers in Fair and Consistent Grading of Open-Ended Questions
- 2 July 2026
- Published by Springer Nature
- p. 83-95
Criterium: Assisting Teachers in Fair and Consistent Grading of Open-Ended Questions
- 1 July 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 243-248
NOESIS: An Exploratory Framework for AI-Supported Metacognitive Learning
- 1 July 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 243-248
NOESIS: An Exploratory Framework for AI-Supported Metacognitive Learning
- 4 February 2026
- Published by Springer Nature
- p. 141-152
Learning Analytics Through Generative AI: An Exploratory Study
- 4 February 2026
- Published by Springer Nature
- p. 141-152
Learning Analytics Through Generative AI: An Exploratory Study
- Open Access
- 12 January 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Network and Service Management
- Vol. 23, 1891-1912
Assurance and Conflict Detection in Intent-Based Networking: A Comprehensive Survey and Insights on Standards and Open-Source Tools
Intent-Based Networking (IBN) enables operators to specify high-level outcomes while the system translates these intents into concrete policies and configurations. As IBN deployments grow in scale, heterogeneity and dynamicity, ensuring continuous alignment between network behavior and user objectives becomes both essential and increasingly difficult. This paper provides a technical survey of assurance and conflict detection techniques in IBN, with the goal of improving reliability, robustness, and policy compliance. We first position our survey with respect to existing work. We then review current assurance mechanisms, including the use of AI, machine learning, and real-time monitoring for validating intent fulfillment. We also examine conflict detection methods across the intent lifecycle, from capture to implementation. In addition, we outline relevant standardization efforts and open-source tools that support IBN adoption. Finally, we discuss key challenges, such as AI/ML integration, generalization, and scalability, and present a roadmap for future research aimed at strengthening robustness of IBN frameworks.
- 12 January 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Network and Service Management
- Vol. 23, 1891-1912
Open AccessAssurance and Conflict Detection in Intent-Based Networking: A Comprehensive Survey and Insights on Standards and Open-Source Tools
Intent-Based Networking (IBN) enables operators to specify high-level outcomes while the system translates these intents into concrete policies and configurations. As IBN deployments grow in scale, heterogeneity and dynamicity, ensuring continuous alignment between network behavior and user objectives becomes both essential and increasingly difficult. This paper provides a technical survey of assurance and conflict detection techniques in IBN, with the goal of improving reliability, robustness, and policy compliance. We first position our survey with respect to existing work. We then review current assurance mechanisms, including the use of AI, machine learning, and real-time monitoring for validating intent fulfillment. We also examine conflict detection methods across the intent lifecycle, from capture to implementation. In addition, we outline relevant standardization efforts and open-source tools that support IBN adoption. Finally, we discuss key challenges, such as AI/ML integration, generalization, and scalability, and present a roadmap for future research aimed at strengthening robustness of IBN frameworks.
- Open Access
- 10 October 2025
- Published by Elsevier in International Journal of Artificial Intelligence in Education
- Vol. 35 (6) , 4137-4140
Guest Editorial: Special Issue on “Bridging Futures: The Convergence of Technology Enhanced Learning and Generative AI”
- 10 October 2025
- Published by Elsevier in International Journal of Artificial Intelligence in Education
- Vol. 35 (6) , 4137-4140
Open AccessGuest Editorial: Special Issue on “Bridging Futures: The Convergence of Technology Enhanced Learning and Generative AI”
- 17 July 2024
- Published by Springer Nature
- p. 155-169
Artificial Intelligence and Learning of Students with Dyslexia: A Brief Review
- 17 July 2024
- Published by Springer Nature
- p. 155-169
Artificial Intelligence and Learning of Students with Dyslexia: A Brief Review
- 17 July 2024
- Published by Springer Nature
- p. 79-93
EduPort: An Intelligent Learning System Based on Deep Learning - A Preliminary Evaluation
- 17 July 2024
- Published by Springer Nature
- p. 79-93
EduPort: An Intelligent Learning System Based on Deep Learning - A Preliminary Evaluation