6G-DALI’s Participation in the IEEE Conference on Network Functions Virtualization and Software-Defined Networking

By /

The 6G-DALI project, the first EU enabler platform for automated Artificial Intelligence solutions for 6G networks, continues to actively advance its dissemination strategy. It successfully participated in theIEEE Conference on Network Functions Virtualization and Software-Defined Networking (#IEEE_NFV_SDN_2025), held in Athens, offering an excellent opportunity to showcase the project’s first scientific contributions and initial results.

During the conference, the 6G-DALI consortium showcased the following key presentations reflecting the project’s progress and innovation:

  • “Applying Value-based and Social Acceptance of Technology methodologies in the development of 6G Proof-of-Concepts” by Luigi Briguglio (CyberEthics Lab, Italy), Carmela Occhipinti and Lucas Pereira Carwile (CyberEthics Lab., Italy), Francesca Morpurgo (CyberEthics Lab, Italy)
  • “Unlocking the Value of 6G Datasets: Business Models, Market Potential, and API-Driven Monetization for Telco Operators” by Michail Rantopoulos (OTE, Greece)
  • “Towards Secure and Interoperable Data Spaces for 6G: The 6G-DALI Approach” by Dimitrios Amaxilatis (Spark Works Ltd., Ireland & University of Patras, Greece), Themistoklis Sarantakos (Spark Works Ltd., Ireland), Nikolaos Tsironis (Spark Works Ltd, Ireland), Vasileios Theodorou (Intracom S.A. Telecom Solutions, Greece) and Christos Verikoukis (University of Patras, Greece)
  • “Foundation for Data Governance in 6G” by Lucía Cabanillas Rodríguez (Telefónica Innovación Digital, Spain), Diego Lopez (Telefonica, Spain) and Ignacio Dominguez (Telefonica ID, Spain)
  • “Initial DataOps Architecture for 6G-DALI” by Vasiliki Parousidou (Intracom Telecom, Greece), Eleni Zarogianni and Vasileios Theodorou (Intracom S.A. Telecom Solutions, Greece)

These presentations emphasized the innovation and uniqueness of the proposed end-to-end AI framework, which automates the entire lifecycle of AI/ML experimental process, from on-demand data generation and management (DataOps) to automated model training and deployment (MLOps).

The project’s successful presence at the conference is the result of the dedication and collaboration of all consortium members, who continue to actively contribute to the implementation of this pioneering initiative.

Scroll to Top