Invitation: FLICS 2025 - Symposium on Federated Learning and Intelligent Computing Systems

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CFP: Federated Learning and Intelligent Computing Systems (FLICS 2025)

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Sep 22, 2025, 6:07:07 PM (7 days ago) Sep 22
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Dear Colleague,

I am pleased to invite you to contribute your valuable research to the 2025 Symposium on Federated Learning and Intelligent Computing Systems (FLICS 2025), co-located with FLLM 2025.

Please find the attached Call for Papers for full details. We look forward to receiving your submission and hope you will join us in this exciting event.

If you have any questions, feel free to reach out.

Best regards,
Sadi Alawadi
On behalf FLICS of the orgnizing committee

CFP: The 2025 Symposium on Federated Learning and Intelligent Computing Systems (FLICS 2025)

A Hybrid Event

Technically Co-Sponsored by IEEE Austrian Section

https://intelligent-systems.net/flics/

Co-Located with the 3rd International Conference on Foundation and Large Language Models (FLLM2025)

Theme: Federated Learning and Its Applications
[Vienna, Austria] --- [25-28 November, 2025]

Scope

The Federated Learning and Intelligent Computing Systems (FLICS) symposium brings together researchers, practitioners, and industry leaders to explore the convergence of federated learning with intelligent computing systems, edge AI, and autonomous workflows. As we advance toward 6G networks, pervasive edge intelligence, and decentralized cyber-physical systems, the need for collaborative, privacy-preserving learning approaches has never been more critical.

Our conference focuses on the intersection of federated learning systems with emerging intelligent computing paradigms, including agentic AI workflows, edge intelligence, digital twin technologies, mobile computing, and distributed machine learning. We aim to address the fundamental challenges of engineering and deploying scalable, secure, and efficient federated learning systems across diverse computational environments in various application domains, including health, energy management, industrial automation, and smart cities.

FLICS 2025 provides a unique platform for interdisciplinary collaboration, bridging theoretical foundations and practical implementations. The symposium welcomes contributions from both researchers and practitioners in the field of FL.

Topics of Interest

We invite submissions addressing, but not limited to, the following areas:

Federated Learning Systems & Edge Intelligence

  • Challenges of FL systems deployment in production environments
  • FL systems automation and self-tuning capabilities
  • Scalable federated learning architectures for large-scale deployments
  • Cross-silo and cross-device federated learning systems
  • Hardware-aware and resource-efficient federated learning
  • Communication-efficient FL (quantization, sparsification, compression techniques)
  • FL under client mobility, heterogeneity, and intermittent connectivity
  • Network-aware optimization and system-level co-design for FL
  • Benchmark and evaluation frameworks for FL systems in mobile/wireless environments
  • FL deployment in UAVs, mobile edge clouds, and autonomous systems

Agentic Workflows and Collaborative AI

  • Federated learning for agentic AI systems and autonomous workflows
  • Collaborative learning in multi-agent environments
  • Privacy-preserving agent-to-agent communication and coordination
  • Federated training of foundation models for agentic applications
  • Distributed learning for tool-use optimization and workflow adaptation
  • User-agent interaction personalization through federated approaches

Privacy, Security, and Trust

  • Privacy-enhancing technologies for federated learning
  • Secure aggregation protocols and cryptographic methods
  • Trustworthy and explainable federated learning systems
  • Resilient and robust FL systems against attacks
  • Privacy-utility trade-offs in distributed learning
  • Auditable and interpretable federated learning frameworks

Mobile Computing & Wireless Networks

  • Federated learning protocols for mobile, vehicular, and edge networks
  • FL in 6G networks and next-generation wireless systems
  • Multi-agent and swarm intelligence-based federated learning
  • Energy-aware and communication-efficient federated intelligence
  • Dynamic network topologies and adaptive FL protocols
  • Distributed inference and online learning for mobile networks
  • Cross-layer optimization for federated learning in wireless systems
  • Quality of service and latency-aware federated learning

Digital Twins & Cyber-Physical Systems

  • Federated intelligence for digital twin ecosystems
  • Digital twin generation and maintenance in distributed networks
  • Real-time federated learning for cyber-physical system monitoring
  • Distributed digital twins for smart cities and industrial IoT
  • Federated anomaly detection and predictive maintenance
  • Live model updating and synchronization in digital twin networks
  • Edge intelligence for decentralized digital twin ecosystems
  • Federated optimization for cyber-physical system control

Applications and Real-World Deployments

  • Smart cities and urban computing applications
  • Autonomous vehicles and intelligent transportation systems
  • Industrial IoT and manufacturing intelligence
  • Healthcare and medical federated learning systems
  • Financial services and fraud detection
  • Swarm robotics and distributed autonomous systems
  • Environmental monitoring and sustainability applications
  • Real-world case studies and deployment experiences
  • Economic models and incentive mechanisms for data federations
  • Regulatory compliance and legal frameworks (GDPR, EU AI Act, etc.)

Emerging Paradigms & Future Directions

  • Continual and lifelong learning in federated settings
  • Few-shot and zero-shot federated learning
  • Federated meta-learning and transfer learning
  • Neural architecture search in federated environments
  • Generative AI and federated learning convergence
  • Quantum-enhanced federated learning
  • Federated foundation models and large-scale pre-training
  • Neuromorphic computing and federated learning
  • Blockchain and distributed ledger technologies for FL
  • Sustainable and green federated learning approaches

Submission Types

  • Research Papers (up to 8 pages): novel methods/systems with rigorous evaluation.
  • Short Papers (up to 6 pages): promising early results, negative results with analysis, replication.

Format: Paper format

All papers should be in PDF format. Please make use of the appropriate IEEE template for conference proceedings to prepare your revised manuscript. Failure to do so may result in excluding your paper from the conference proceedings.

IEEE Word template can be found here (IEEE Conference Word Template).

IEEE Latex template can be found here (IEEE Conference Latex Template).

IEEE Overleaf Latex template can be found here (IEEE Overleaf Conference Latex Template).

Important Dates

  • Paper submission: October 1, 2025
  • Notification of acceptance: October 20, 2025
  • Camera-ready deadline: November 1, 2025

All deadlines are in Anywhere on Earth (AoE) time.

Submission Portal

Papers should be submitted through Easychair at: https://easychair.org/my/conference?conf=fllm2025

For submission guidelines, please visit: https://intelligent-systems.net/flics/

Contact Information

For questions about submissions, please contact:

We look forward to receiving your contributions and to seeing you at FLICS 2025!



CFP: Federated Learning and Intelligent Computing Systems (FLICS 2025)

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Sep 23, 2025, 2:17:35 AM (7 days ago) Sep 23
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CFP: Federated Learning and Intelligent Computing Systems (FLICS 2025)

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Sep 25, 2025, 4:30:52 AM (5 days ago) Sep 25
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