Call For Papers
The ICFLDS aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.
The conference highlights advancements in Artificial Intelligence,Data Science,Machine Learning, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.
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
Assessment
Submissions will be assessed for originality, innovation, and relevance. Accepted papers will be presented at the conference and considered for publication opportunities in reputed academic platforms.
Registration
Participants are requested to complete the registration process following acceptance of their paper. Registration ensures inclusion in the conference schedule and official records.
Publication
All accepted manuscripts will be eligible for publication consideration in conference proceedings and associated academic journals.