27–30 October 2026  |  Paris, France

The 4th International Conference on Federated Learning Technologies and Applications (FLTA 2026)

Join us for FLTA 2026, the premier conference on Federated Learning technologies and applications — advancing AI collaboration, privacy, and innovation.

Paper Submission Important Dates
Federated Learning Summer School In conjunction with AGCS AI 2026 In cooperation with IEEE France Section

Location

Paris, France

Submission Deadline

August 5, 2026 Final and firm

Conference Date

27–30 October 2026

Supported by

IEEE Computational Intelligence Society
IEEE Communications Society
IEEE Computer Society
IEEE France Section
Université Paris 1 Panthéon-Sorbonne
ETIS Laboratory
CY Cergy Paris Université
Université Paris 8
Umeå University
NVIDIA

About The Conference

The 4th International Conference on Federated Learning Technologies and Applications (FLTA 2026) is a premier venue for the timely publication of FL management, systems, services, technologies, and applications. FLTA 2026 aims to provide attendees with a comprehensive understanding of FL communication, computing, and system requirements. Through keynote speeches, panel discussions, and presentations, attendees can engage with leading experts and learn about the latest developments and future trends in the field.

FLTA 2026 focuses on fostering an understanding of FL, identifying technical challenges, and exploring potential solutions, including distributed optimization, privacy-preserving techniques, intelligent learning algorithms, personalized FL, communication efficiency approaches, Secure and Trustworthy FL, open challenges, and recent trends and opportunities in FL. We welcome submissions addressing the important challenges (see the topics below) and presenting novel research or experimentation results with system or network-related case studies. Survey papers that offer a perspective on related work and identify key challenges for future research will be considered as well.

  • Federated Learning frameworks
  • Federated Learning aggregation algorithms
  • Federated Learning applications
  • Federated Learning deployment architectures
  • Privacy-preserving FL techniques
  • Federated Learning communication efficiency
  • Federated Learning modelling and simulation tools
  • Federated Learning datasets and benchmarking
  • Challenges and advancements
  • Federated Learning for emerging technologies

In cooperation with IEEE France Section

We acknowledge the involvement of the IEEE France Section in supporting the community around FLTA 2026.

Meet Our Sponsors

Our sponsors are the driving force behind the success of this event, bringing their innovation and support to the forefront. Explore the contributions of these incredible organizations and how they are shaping the future of Federated Learning.

Become a Sponsor