International Conference on Federated Learning and Data Science ICFLDS

Call For Papers

The ICFLDS bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Artificial Intelligence, Data Science, Machine Learning , encouraging applied research, case studies, and industry-driven innovations.

Authors are invited to submit papers addressing, but not limited to, the following areas:

Federated learning for privacy-preserving AI

Challenges in federated learning implementation

Applications of federated learning in healthcare

Data sharing in federated learning systems

Federated learning for edge computing

Ethical considerations in federated learning

Federated learning in financial services

Real-world case studies of federated learning

Federated learning for IoT devices

Performance evaluation of federated learning models

Collaborative learning without data centralization

Federated learning in mobile applications

Data security in federated learning frameworks

Future trends in federated learning research

Federated learning for natural language processing

Integrating federated learning with blockchain

Federated learning for personalized AI models

Scalability issues in federated learning systems

Federated learning in smart cities

Impact of federated learning on data ownership

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in reputed journals and conference proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

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Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

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Hybrid Event