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<p><b>Workshop FLEdge-AI @ ACM MOBICOM 2025 <i><u>(A* ICORE
ranking)</u><br>
</i> </b></p>
<p><b>Organizers and Chairs</b><br>
</p>
Francesco Piccialli (University of Naples Federico II, Italy)<br>
David Camacho (Universidad Politécnica de Madrid, Spain)<br>
Fabio Giampaolo (University of Naples Federico II, Italy)<br>
Jon Crowcroft (University of Cambridge, UK)<br>
Liu Wang (Hong Kong Polytechnic University, China)<br>
Yuchao Zhang (Beijing University of Posts and Telecommunications,
China)<br>
<p><b>Official Link:</b> <a class="moz-txt-link-freetext"
href="https://conferences.cis.um.edu.mo/ieeebigdata2025/special_sessions.html#federated">https://edgeai2025.github.io/</a></p>
<p><b>Linked Special Issue:</b>
<a class="moz-txt-link-freetext" href="https://onlinelibrary.wiley.com/page/journal/14680394/homepage/call-for-papers/si-2025-000707">https://onlinelibrary.wiley.com/page/journal/14680394/homepage/call-for-papers/si-2025-000707</a><br>
</p>
<p><b>Aim and Scope</b><br>
<br>
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. </p>
<p>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.<br>
<b><br>
Topics of interest include, but are not limited to, the
following:</b></p>
<p>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. </p>
<p>We focus on all aspects of edge network, data privacy and
federated technologies, including but not limited to the
following:<br>
</p>
<ul>
<li>Federated Learning protocols for mobile, vehicular, and edge
networks</li>
<li>Communication-efficient FL (e.g., quantization,
sparsification, gossip-based)</li>
<li>FL under client mobility, heterogeneity, and intermittent
connectivity</li>
<li>Privacy and security in mobile FL (e.g., differential
privacy, secure aggregation)</li>
<li>Personalization and federated transfer learning</li>
<li>Multi-agent and swarm intelligence-based FL</li>
<li>Benchmarking FL in wireless/mobile environments</li>
<li>Network-aware optimization and system-level co-design for FL</li>
<li>FL deployment in UAVs, mobile edge clouds, and autonomous
systems</li>
</ul>
<p> <b>Important Dates</b></p>
</div>
<div class="moz-text-html" lang="x-unicode">Workshop Paper
Submissions: July 25, 2025<br>
Notification of acceptance: September 15, 2025<br>
Camera-ready Workshop Papers: October 10, 2025<br>
Workshop Dates: November 8, 2025<br>
<p><b>Kind Regards</b><br>
</p>
<pre class="moz-signature" cols="72">--
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: <a
class="moz-txt-link-freetext" href="https://www.labdma.unina.it">https://www.labdma.unina.it</a>
Web: <a class="moz-txt-link-freetext"
href="http://wpage.unina.it/francesco.piccialli/">http://wpage.unina.it/francesco.piccialli/</a>
Google Scholar: <a class="moz-txt-link-freetext"
href="https://scholar.google.it/citations?user=CLNn_9gAAAAJ&hl=it">https://scholar.google.it/citations?user=CLNn_9gAAAAJ&hl=it</a>
Institutional web: <a class="moz-txt-link-freetext"
href="https://www.docenti.unina.it/francesco.piccialli">https://www.docenti.unina.it/francesco.piccialli</a></pre>
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