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Luca Borgianni
Also published under:
Affiliation
University of Pisa, Italy
Topic
Quality Of Experience,Wide Area Network,Control Plane,Low Earth Orbit,Reinforcement Learning Algorithm,Reward Function,Service Quality,Deep Q-learning,Earth Orbit,Enterprise Network,Learning Algorithms,Network Infrastructure,Packet Loss,Performance Guarantees,Remote Areas,Software-defined Wide Area Network,Terrestrial Networks,5G Networks,5G Technology,6G Networks,Advances In Communication Technologies,Application Layer,Arduino,Audio Data,Audio Files,Audio Recordings,Autonomous Vehicles,Availability Of Technologies,Average Delay,Basis For Further Research,Bee Colonies,Bee Species,Beekeepers,Branch Offices,Broadband Internet,Business,Celestial Bodies,Central Server,Centralized Approach,Classical Channel,Cloud-based Applications,Combination Of States,Communication Delay,Communication Systems,Community Spaces,Complex Configurations,Complex Network,Computational Capabilities,Control Network,Convolutional Neural Network,
Biography
Luca Borgianni received Bachelor's and Master's degrees in Telecommunication Engineering from the University of Pisa (Italy) in 2020 and 2022, respectively. He is currently a Ph.D. student in the Department of Information Engineering at the same university. His studies and research activities focus on traffic measurement and network control for high QoE in inter-active multimedia applications. His current research interests are in the field of Software-Defined Wide Area Networks with a particular focus on Reinforcement Learning algorithms to improve QoS. He is also involved in support of teaching activities for FPGA laboratories and Mininet laboratories. Other research interests include Network traffic prediction, Quantum Networking, and Networked Music Performance.