The 2nd International Conference on Federated Learning and Distributed Intelligence (FLDI 2027)

March 15-18, 2027, USA

Scope & Topics

The 2nd International Conference on Federated Learning and Distributed Intelligence (FLDI 2027) provides an international forum for researchers, academics, industry professionals, and practitioners to present and discuss recent advances in federated learning, distributed artificial intelligence, collaborative machine learning, and intelligent decentralized systems.

Federated learning and distributed intelligence are rapidly emerging as key technologies for enabling collaborative artificial intelligence across decentralized and heterogeneous computing environments. These technologies support privacy, scalability, data governance, and efficient use of distributed resources.

FLDI 2027 welcomes original research and practical contributions covering areas such as federated and decentralized learning algorithms, privacy-preserving machine learning, distributed optimization, edge intelligence, federated large language models, communication-efficient learning, security and robustness, resource management, heterogeneous and personalized federated learning, and real-world applications.

Topics of Interest include, but are not limited to:

• Federated Learning Foundations and Algorithms
• Federated Optimization and Learning Algorithms
• Personalized and Heterogeneous Federated Learning
• Asynchronous and Decentralized Federated Learning
• Communication-Efficient Federated Learning
• Convergence, Scalability, and Performance Analysis
• Distributed and Edge Intelligence
• Edge AI and Distributed Machine Learning
• Collaborative and Decentralized Intelligence
• Intelligent Edge-Cloud Systems
• Resource-Aware Distributed Learning
• Multi-Agent and Swarm Intelligence
• Privacy, Security, and Trustworthy Federated Learning
• Privacy-Preserving Machine Learning
• Differential Privacy and Secure Aggregation
• Attacks, Defenses, and Adversarial Robustness
• Trust, Reputation, and Incentive Mechanisms
• Blockchain-Enabled Federated Learning
• Federated Learning for Generative AI and Large Models
• Federated Large Language Models
• Federated Foundation and Multimodal Models
• Distributed Training and Fine-Tuning of Large Models
• Parameter-Efficient Federated Learning
• Federated Generative AI and AI Agents
• Systems, Platforms, and Resource Management
• Federated Learning Architectures and Frameworks
• Communication and Network Optimization
• Client Selection and Resource Allocation
• Energy-Efficient Federated Learning
• Deployment, Orchestration, and Benchmarking
• Applications of Federated and Distributed Intelligence
• Healthcare and Biomedical Applications
• IoT, Smart Cities, and Intelligent Transportation
• Cybersecurity and Intrusion Detection
• Autonomous Systems and Robotics
• 5G/6G Networks, Industrial Systems, and Smart Environments

Important Dates

Abstract Submission	:	N/A
Full Paper Submission	:	November 20, 2026
Accept/Reject Notification	:	January 20, 2027
Final Manuscript Submission	:	February 10, 2027
Conference Date	:	March 15-18, 2027
Conference Location	:	USA

Contact:
The 2nd International Conference on Federated Learning and Distributed Intelligence (FLDI 2027)
Emerging Technology Network
Email: emergingtechnetwork@gmail.com

Conference Website:
[https://emergingtechnet.org/FLDI2027/index.php](https://emergingtechnet.org/FLDI2027/index.php "https://emergingtechnet.org/FLDI2027/index.php")

User Name : Zebi
Posted 24-09-2026 on 22:35:20

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