Connectionists: CFP: SS DSAA'25 - Collaborative AI: Advancing Federated Learning Across Disciplines

[Frank-Michael Schleif]

* Apologies for multiple copies. Please forward to anybody who might be
interested, thanks! *

DSAA 2025 SPECIAL SESSION
‘Collaborative AI: Advancing Federated Learning Across Disciplines’
09 - 13 October 2025, Birmingham, UK
https://dsaa.ieee.org/2025


This special session explores federated machine learning in increasingly
complex distributed environments. As data becomes distributed among
numerous users and cannot
be centrally collected due to privacy constraints, new challenges
emerge. These include
learning in heterogeneous systems, effective communication for model
updates, and
representation of distributed models. We focus on federated learning
variants, model
compression, adaptive aggregation techniques, and privacy preservation
approaches including
differential privacy. The session encourages research on deep learning
applications in federated
contexts, particularly in IoT, recommendation systems, medicine,
automotive, sensor
networks, and text processing, with emphasis on balancing privacy,
efficiency, and
performance.

AIMS AND SCOPE

We particularly welcome submissions that bridge research communities and
foster interdisciplinary collaboration. Our special session seeks papers
presenting novel methods at the intersection of federated learning,
distributed intelligence,
computational intelligence, and machine learning that promote dialogue
across traditional research
boundaries.

Topics include but are not limited to:

● Learning in heterogeneous and distributed systems
● Effective communication protocols for model updates in federated
environments
● Model compression and adaptive model aggregation techniques
● Representation learning and distributed model architectures
● Approximation methods for distributed data analysis
● Federated learning algorithms and variants (Split learning, Gossip
Learning,
decentralized approaches)
● Shapley value attribution and Shapley interactions for model
interpretation in
federated settings
● Multi-modality and multi-view approaches in federated learning
● Security and privacy preservation in federated environments
● Differential privacy techniques for federated systems
● Applications of deep learning in federated contexts
● Resource-efficient federated learning for constrained environments
● Data analysis and pattern recognition approaches for non-stationary and
distributed
environments

Deadline: 02.05.2025 (everywhere on earth)
Submission via:
https://openreview.net/group?id=IEEE.org/DSAA/2025

SPECIAL SESSION ORGANIZERS
Frank-Michael Schleif, Technical UAS Wuerzburg-Schweinfurt, Germany
Mirko Polato, Università di Torino, Italy
Barbara Hammer, University of Bielefeld, Germany
Manuel Röder, Technical UAS Wuerzburg-Schweinfurt, Germany

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Prof. Dr. rer. nat. habil. Frank-Michael Schleif
School of Computer Science
Technical University of Applied Sciences Würzburg-Schweinfurt
Sanderheinrichsleitenweg 20
Raum I-3.35
Tel.: +49(0) 931 351 18127
97074 Würzburg

Honorable Research Fellow
The University of Birmingham
Edgbaston
Birmingham B15 2TT
United Kingdom
-
email: frank-michael.schleif at thws.de
http://promos-science.blogspot.de/
https://www.techfak.uni-bielefeld.de/~fschleif/
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