Nicola Piovesan is a Senior Researcher at Huawei Technologies, in Paris, France. His research activity focuses on generative AI in next-generation telecom networks, large-scale network modeling, and green networking.
He earned his PhD degree in Network Engineering at the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, in 2020, and he received the BSc degree in Information Engineering and the MSc in Telecommunication Engineering from the University of Padova, Italy, in 2013 and 2016, respectively.
From 2016 to 2019, he was an Assistant Researcher at the Mobile Networks Department of the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC). In 2016, he has been awarded with a European Union’s Marie Skłodowska-Curie fellowship to work as early-stage researcher in the EU H2020 MSCA SCAVENGE (Sustainable Cellular Networks Harvesting Ambient Energy) project.
In 2019, he was at Nokia Bell Labs as a visiting researcher in the Small Cells Research Department.
Dr. Piovesan has contributed to multiple industrial and academic projects, published over 50 research articles, and is co-inventor of more than 10 patents. His work has been recognized with the Huawei GTS President Award (2021) and the Huawei Quality Star Award (2024), acknowledging his successful translation of research into real-world product development. He is actively involved in collaborative initiatives on AI and energy efficiency in next-generation networks.
Paris, France
Leading research on agentic AI architectures and LLM applications for autonomous network operations, optimization, and intent-driven management — including multi-agent planning, benchmarking methodologies for LLM reasoning in telecom scenarios, and contributions to patents, standardization, and high-impact publications.
Paris, France
Machine learning for power consumption estimation in large-scale networks and spatio-temporal forecasting via graph neural networks to optimize energy-saving features — contributing to multiple publications and patents on AI-enhanced network management.
Dublin, Ireland
Deep reinforcement learning frameworks for autonomous small cell control and mathematical modeling of network deployments to optimize energy-capacity trade-offs.
Barcelona, Spain
Doctoral research on energy efficiency and sustainable wireless networks, funded by the EU H2020 Marie Skłodowska-Curie SCAVENGE project. Thesis focused on resource allocation in green cellular networks with ambient energy harvesting.
Barcelona, Spain
Assistant researcher at the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Mobile Networks Department. Worked on energy-aware resource management and sustainable 5G networks within the EU SCAVENGE project.
Padova, Italy
Padova, Italy
