معرفی
Antoine LAVIGNOTTE is a Lecturer at Telecom SudParis' NeSS (Network Security and Services) department. His research focuses on machine learning applications in telecommunications, optical networks, and network security. He has contributed to advancements in fault prediction, reinforcement learning for optical systems, and quality of experience (QoE) in multimedia streaming.
Education:
- PhD in Multimedia (2014), Jean Monnet University - Saint-Etienne: Thesis titled 'Considering the quality of user experience within adaptive HTTP streaming protocols.'
Research Interests:
- MACHINE LEARNING APPLICATIONS: Network fault prediction, optical amplifier control, and dynamic resource allocation in optical networks.
- NETWORK SECURITY: 5G slice embedding security and multi-provider network virtualization.
- QUALITY OF EXPERIENCE: User-centric metrics in adaptive streaming and 3D multimedia systems.
Recent Trends in Publications: His work emphasizes machine learning-driven solutions for telecom infrastructure resilience, optical network optimization, and security frameworks for next-generation networks. Collaborations with institutions like SAMOVAR highlight his engagement in applied research.
Advising: Supervised Killian Murphy's 2024 thesis on predictive maintenance in telecom networks. Active in guiding interdisciplinary projects at Telecom SudParis.
Labs & Teams: Member of SAMOVAR lab, a leading research group in network sciences and telecommunications at Telecom SudParis.
