Invitation to Submit
제출 안내
The International Conference on Federated Learning and Data Science , organized by the Korean Society for Academic Advancement (KSAA), invites original and high-quality research contributions from researchers, academicians, and professionals across all disciplines. Submissions are accepted in the form of research papers, case studies, and review articles aligned with the conference themes and academic focus areas.
International Conference on Federated Learning and Data Science , 한국학술진흥학회(KSAA)가 주최하는 본 학술대회는 다양한 분야의 연구자, 학자 및 전문가들로부터 우수한 연구 논문을 모집합니다. 논문, 사례 연구 및 리뷰 논문 등 학술대회 주제에 부합하는 연구 결과를 제출할 수 있습니다.
Research Papers
연구 논문
Case Studies
사례 연구
Review Articles
리뷰 논문
Research Areas
연구 분야
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
Review & Acceptance
심사 및 채택
All submissions will undergo a peer review process. Accepted papers may be presented at the conference and considered for further academic dissemination.
모든 제출 논문은 동료 심사 과정을 거치며, 채택된 논문은 학술대회 발표 및 추가 학술 확산의 기회를 갖게 됩니다.