International Conference on Federated Learning and Data Science
(ICFLDS-26)

31st Dec 2026 - 1st Jan 2027,
Washington DC, USA

Join as Attendee Submit Your Abstract/Paper

Complete Registration → Browse conference registration categories.
Quality articles will be published in well reputed journals like Scopus Indexed or Web of Science **

Pre-Enrollment

1st December 2026

Final Paper Submission

6th December 2026

Registration Deadline

16th December`2026

Conference Date

31st Dec 2026 - 1st Jan 2027

Call for Papers

The International Conference on Federated Learning and Data Science invites researchers, academicians, industry experts, and practitioners to submit original and high-quality research contributions. This conference serves as a global platform for presenting innovative ideas, exchanging knowledge, and fostering interdisciplinary collaboration.

Focusing on key research areas such as Artificial Intelligence,Data Science,Machine Learning, the conference aims to bridge theoretical advancements with real-world applications.

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

01
Federated Learning For Privacy-preserving Ai
02
Challenges In Federated Learning Implementation
03
Applications Of Federated Learning In Healthcare
04
Data Sharing In Federated Learning Systems
05
Federated Learning For Edge Computing
06
Ethical Considerations In Federated Learning
07
Federated Learning In Financial Services
08
Real-world Case Studies Of Federated Learning
09
Federated Learning For Iot Devices
10
Performance Evaluation Of Federated Learning Models
11
Collaborative Learning Without Data Centralization
12
Federated Learning In Mobile Applications
13
Data Security In Federated Learning Frameworks
14
Future Trends In Federated Learning Research
15
Federated Learning For Natural Language Processing
16
Integrating Federated Learning With Blockchain
17
Federated Learning For Personalized Ai Models
18
Scalability Issues In Federated Learning Systems
19
Federated Learning In Smart Cities
20
Impact Of Federated Learning On Data Ownership
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All submissions undergo a rigorous peer-review process conducted by subject matter experts to ensure originality and technical quality. Accepted papers will be considered for publication in reputed journals and conference proceedings.

Conference Registration

To confirm your participation and secure your presentation slot, authors of accepted papers must complete the registration. Early registration is highly recommended to enjoy discounted fees.

Register Now to Confirm Participation
Publication & Submission

Present your findings to a global audience. All accepted papers are eligible for publication in ISER-affiliated journals and conference proceedings, providing you with maximum academic visibility.

Submit Your Paper for Review