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TrustFL-SIS 2026 : Trustworthy Federated Learning for Smart Industrial Systems

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Link: https://modal-unina.github.io/TrustFL-SIS/
 
When Nov 12, 2026 - Nov 15, 2026
Where Shenyang, China
Submission Deadline Aug 27, 2026
Notification Due Sep 18, 2026
Final Version Due Oct 5, 2026
Categories    federated learning   privacy   digital twins   industrial ai
 

Call For Papers

TrustFL-SIS 2026
Trustworthy Federated Learning for Smart Industrial Systems
Half-Day Workshop at IEEE ICDM 2026

TrustFL-SIS 2026 invites original research contributions on trustworthy Federated Learning for real-world industrial systems.

Industrial applications increasingly rely on distributed, heterogeneous, and privacy-sensitive data that cannot always be centralized. Federated Learning provides a promising approach to collaborative model training without requiring the exchange of raw data. However, its adoption in safety-critical industrial environments requires stronger guarantees of reliability, security, privacy, fairness, explainability, and sustainability.

The workshop aims to bring together researchers and practitioners from academia and industry to discuss recent advances, practical challenges, and emerging research directions in trustworthy Federated Learning for industrial data mining and intelligent systems.

Topics of interest include, but are not limited to:

Trustworthy and explainable Federated Learning
Robust and fair learning under non-IID and heterogeneous data
Privacy-preserving Federated Learning and secure aggregation
Security threats, attacks, and defence mechanisms
Federated time-series analysis and sensor fusion
Predictive maintenance, anomaly detection, and process optimization
Federated Learning for edge computing and the Industrial Internet of Things
Integration of Digital Twins and Federated Learning
Sustainable and communication-efficient federated optimization
Benchmarks and evaluation frameworks
Applications in smart manufacturing, smart healthcare, smart cities, and intelligent mobility
Industrial case studies and real-world deployments

The workshop welcomes the following types of contributions:

Full research papers: up to 8 pages
Short or position papers: up to 4 pages

Papers must be written in English, submitted in PDF format, and prepared according to the IEEE two-column conference template.

All submissions will undergo peer review and will be evaluated based on originality, technical quality, clarity, relevance, and potential contribution to the workshop.

Selected high-quality papers may be invited to submit substantially extended versions for consideration in a special issue of Expert Systems, published by Wiley.

Invited manuscripts must contain substantial new material and will undergo the journal’s standard peer-review process.

Paper submission deadline: August 27, 2026
Notification of acceptance: September 18, 2026
Camera-ready submission deadline: October 5, 2026
Workshop: in conjunction with IEEE ICDM 2026


Workshop website:

https://modal-unina.github.io/TrustFL-SIS/

For questions regarding submissions or participation, please contact the organizing committee using the contact information provided on the workshop website.

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