Connectionists: Call For Papers - Federated Learning and Edge AI for Privacy and Mobility (FLEdge-AI) @ ACM MOBICOM 2025

[Francesco Piccialli]

*Workshop FLEdge-AI @ ACM MOBICOM 2025 /_(A* ICORE ranking)_
/ *

*Organizers and Chairs*

Francesco Piccialli (University of Naples Federico II, Italy)
David Camacho (Universidad Politécnica de Madrid, Spain)
Fabio Giampaolo (University of Naples Federico II, Italy)
Jon Crowcroft (University of Cambridge, UK)
Liu Wang (Hong Kong Polytechnic University, China)
Yuchao Zhang (Beijing University of Posts and Telecommunications, China)

*Official Link:* https://edgeai2025.github.io/

*Linked Special Issue:* 
https://onlinelibrary.wiley.com/page/journal/14680394/homepage/call-for-papers/si-2025-000707

*Aim and Scope*

The FLEdge-AI 2025 workshop aims to bring together researchers, 
practitioners, and industry leaders to explore the critical intersection 
of Federated Learning (FL), Edge AI, privacy, and mobility. As the 
mobile computing landscape rapidly evolves towards 6G, pervasive edge 
intelligence, and decentralized AI, FL and Edge AI are emerging as 
foundational technologies. They enable privacy-preserving, resilient, 
and distributed machine learning across dynamic, resource-constrained, 
and heterogeneous environments. This workshop will serve as a premier 
forum for discussing the latest research in algorithms, systems, and 
real-world deployments of federated learning and edge AI in mobile and 
wireless scenarios.

We aim to address the pressing technical challenges and opportunities in 
making FL and Edge AI practical and impactful for mobile users and 
applications. Key issues include communication bottlenecks in mobile 
systems, device and statistical heterogeneity, user mobility and dynamic 
network topologies, and ensuring robust privacy and security in open and 
untrusted environments. The goal is to foster innovations that bridge 
the gap between theory and deployment, particularly focusing on how 
these technologies can operate effectively under the constraints of 
mobile networks and edge devices.
*
Topics of interest include, but are not limited to, the following:*

The goal of this FLEdge-AI 2025 Workshop is to bring together 
scientists, researchers, and engineers to identify new problems, latest 
novel topics, and emerging technologies.

We focus on all aspects of edge network, data privacy and federated 
technologies, including but not limited to the following:

  * Federated Learning protocols for mobile, vehicular, and edge networks
  * Communication-efficient FL (e.g., quantization, sparsification,
    gossip-based)
  * FL under client mobility, heterogeneity, and intermittent connectivity
  * Privacy and security in mobile FL (e.g., differential privacy,
    secure aggregation)
  * Personalization and federated transfer learning
  * Multi-agent and swarm intelligence-based FL
  * Benchmarking FL in wireless/mobile environments
  * Network-aware optimization and system-level co-design for FL
  * FL deployment in UAVs, mobile edge clouds, and autonomous systems

*Important Dates*

Workshop Paper Submissions: July 25, 2025
Notification of acceptance: September 15, 2025
Camera-ready Workshop Papers: October 10, 2025
Workshop Dates: November 8, 2025

*Kind Regards*

-- 
Prof. Francesco Piccialli, Ph.D.
DMA - Department of Mathematics and Applications "R. Caccioppoli"
University of Naples Federico II, Italy
Tel. +39 081675787
Head and Scientific Director of M.O.D.A.L group:https://www.labdma.unina.it
Web:http://wpage.unina.it/francesco.piccialli/
Google Scholar:https://scholar.google.it/citations?user=CLNn_9gAAAAJ&hl=it
Institutional web:https://www.docenti.unina.it/francesco.piccialli
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