Connectionists: Call for papers - DSAA'25 - SS - 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


ABSTRACT
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_Sessions

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
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email: frank-michael.schleif at thws.de
http://promos-science.blogspot.de/
https://www.techfak.uni-bielefeld.de/~fschleif/
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