[hpc-announce] The 2nd International Conference on Federated Learning and Intelligent Computing Systems (FLICS 2026)

[FLICS]

[Apologies if you got multiple copies of this invitation]CFP: The 2nd
International Conference on Federated Learning and Intelligent Computing
Systems (FLICS 2026)

https://urldefense.us/v3/__https://flics-conference.org/index.php__;!!G_uCfscf7eWS!b0AhAyQtj9aIlWiZanWtDutCA5o9wx7jyLqzNWWiIg9Dkgue2LIvR2hz_IPGSe7Zgp3qqw0TGiNQdulMqVfkIDI$ 

Valencia, Spain, June 9–12, 2026

Technically Co-sponsored by IEEE Spain Section.

Important: Selected papers will be invited to the Expert Systems or Cluster
Computing Journals.

Conference Scope

The Federated Learning and Intelligent Computing Systems (FLICS) Conference
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.

FLICS 2026 features two main tracks that address complementary aspects of
modern intelligent computing:

Main Track 1 – Federated Learning Systems & Applications

This track focuses on the fundamental challenges and innovations in
federated learning, including scalable architectures, privacy and security
mechanisms, communication efficiency, personalization, edge computing
integration, and real-world deployments. This track addresses the core
technical foundations of federated learning systems and their applications
across diverse domains such as healthcare, finance, industrial IoT, and
smart cities.

Main Track 2 – Intelligent Computing Systems

This track explores cutting-edge technologies and applications in
intelligent computing systems, including large language models, generative
AI, deep learning architectures, agentic AI workflows, digital twins, and
smart city applications. This track bridges the gap between federated
learning and emerging AI paradigms, addressing the systems, infrastructure,
and interdisciplinary applications that drive the next generation of
intelligent computing.

FLICS 2026 provides a unique platform for interdisciplinary collaboration,
bridging theoretical foundations and practical implementations. The
Conference welcomes contributions from both researchers and practitioners
across both tracks, fostering dialogue between specialists in federated
learning and experts in intelligent computing systems.

Important Dates

• Paper submission: February 20, 2026

• Notification of acceptance: April 15, 2026

• Camera-ready deadline: May 5, 2026
Main Track 1 – Federated Learning Systems & ApplicationsFederated Learning
Systems & Edge Intelligence

• Scalable FL architectures and large-scale deployments

• Cross-silo and cross-device federated learning

• Hardware-aware and resource-efficient FL

• Communication-efficient FL (quantization, sparsification, compression)

• FL under client mobility and heterogeneity

• Benchmarks and evaluation frameworks for FL

• FL deployment in UAVs, mobile edge clouds, autonomous systems
Privacy, Security, and Trust in FL

• Privacy-enhancing technologies

• Secure aggregation protocols and cryptographic methods

• Explainable and trustworthy FL

• Resilient FL against adversarial attacks

• Privacy–utility trade-offs

• Auditable FL frameworks
Communication & Resource Efficiency for FL

• Model and gradient compression

• Sparse and adaptive communication

• Energy-efficient FL

• Hierarchical and clustered FL

• Multi-objective optimization
Personalization & Fairness in FL

• Personalized FL

• Fairness-aware FL

• Meta-learning for FL

• Bias mitigation

• Clustered and multi-task FL
Edge Computing, IoT, and Mobile/Wireless FL

• Edge–cloud FL architectures

• IoT orchestration

• FL in 5G/6G and vehicular networks

• Real-time FL systems
Advanced FL Paradigms

• Federated deep learning and GNNs

• Federated reinforcement learning

• Federated generative models

• Neuro-symbolic FL
Applications & Real-World Deployments

• Healthcare and medical AI

• Financial services and risk modeling

• Industrial IoT and predictive maintenance

• Smart cities and infrastructure

• NLP and computer vision via FL
Emerging & Interdisciplinary FL Directions

• Continual and lifelong learning

• Quantum FL

• Neuromorphic FL

• Blockchain for FL

• Sustainable and green FL
Main Track 2 – Intelligent Computing Systems & Emerging AI ParadigmsLarge
Language Models, Generative AI & NLP

• LLM architectures and training

• Prompting, fine-tuning, alignment

• Multi-modal generative AI

• NLP for intelligent assistants

• Evaluation and robustness
Deep Learning & Advanced Intelligent Systems

• Novel deep learning architectures

• Transformers, GNNs, hybrid models

• Continual learning and transfer learning

• Deep reinforcement learning
Agentic AI & Autonomous Workflows

• Agentic AI systems and workflow automation

• Multi-agent systems and collaborative intelligence

• User–agent interaction and personalization
Digital Twins, Cyber-Physical & Intelligent Systems

• Digital twins for industry and cities

• Real-time monitoring and simulation

• Edge AI for CPS
Intelligent Systems for Smart Cities & Urban Computing

• Urban mobility optimization

• Smart energy systems

• Urban sensing and IoT

• AI for emergency response

• Urban digital twins
Systems, Infrastructure & Platforms

• Distributed systems for AI workloads

• Hardware acceleration

• Performance and energy optimization
Applications & Interdisciplinary Case Studies

• Healthcare and life sciences

• FinTech and risk modeling

• Industry 4.0 and robotics

• Education and digital services

• Sustainability and environmental monitoring
Submission Types

• Research Papers: up to 8 pages

• Short Papers: up to 6 pages

• Posters: up to 2 pages

• Artefacts & Demonstrations: up to 6 pages
Contact Information

For submission questions, contact:
Sadi Alawadi – sadi.alawadi at bth.se