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:
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.
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 federated learning specialists and intelligent computing systems experts.
Selected papers with potential for further development may be invited to submit an extended version to a special track in one of the following journals:
The conference features two main tracks. See details below about each track.