Connectionists: CFP: WAFL 2026 @ ECML-PKDD - Deadline Extended

[FRANCA ROCCO DI TORREPADULA]

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WAFL 2026 – Deadline Extended
4th Workshop on Advancements in Federated Learning (WAFL)
Towards Trustworthy Federated Learning
https://wafl2026.di.unito.it/
Co-located with ECML-PKDD 2026, Naples, Italy
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Dear colleagues,
We are pleased to announce that the submission deadline for the 4th Workshop on Advancements in Federated Learning (WAFL 2026) has been extended to June 12th, 2026.
We warmly invite you to submit your work and kindly encourage you to share this call with colleagues and interested researchers.

IMPORTANT DATES
• Submission deadline: June 12th, 2026
• Author notification: July 1st, 2026
• Camera-ready: July 10th, 2026
• Workshop: September 11th, 2026

ABOUT THE WORKSHOP
As machine learning systems become increasingly embedded in society, concerns around privacy, fairness, robustness, and regulatory compliance continue to grow—especially under frameworks such as the GDPR and the European AI Act (2024).
Federated Learning (FL) enables collaborative model training without sharing raw data, but also raises challenges such as adversarial robustness, bias from heterogeneous data, and limited transparency.
WAFL 2026 focuses on Federated Learning, bringing together contributions addressing fairness, privacy, robustness, accountability in decentralized AI and with a major focus on trustworthiness of federated learning systems.

TOPICS OF INTEREST
• Algorithmic and theoretical advances in FL
• FL under non-IID data distributions
• Privacy and security (e.g., differential privacy, adversarial/poisoning attacks, secure aggregation)
• Fairness, interpretability, and explainability in FL
• Decentralized and peer-to-peer FL
• Transparency and accountability
• Regulatory compliance (GDPR, EU AI Act)
• Real-world applications (e.g., healthcare, finance, edge devices)
• Tools and benchmarks for FL

SPECIAL ISSUE
Selected papers will be invited to a special issue on
“Trustworthy and Responsible Federated Learning” in Discover Artificial Intelligence (Springer): https://link.springer.com/collections/fdcjaidaif

SUBMISSION DETAILS
• Long papers: 12 pages + references + supplementary
• Short papers: 6 pages + references + supplementary
• Non-archival submissions allowed
Submissions follow ECML-PKDD guidelines and will undergo double-blind review.
Submission: https://cmt3.research.microsoft.com/User/Login?ReturnUrl=%2FECMLPKDDWT2026%2FSubmission%2FIndex (select WAFL track)
Accepted papers will be presented at the workshop and included (optional) in Springer CCIS proceedings.

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For more information: https://wafl2026.di.unito.it/
Contact: franca.roccoditorrepadula at unina mirko.polato at unito.it roberto.esposito at unito.it mfisichella at l3s.de
Best regards,
WAFL 2026 Organizing Committee

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