Connectionists: [Last CFP-Extended] LODAS 2026 - Learning & Optimization for Distributed AI Systems @ FLICS 2026 (Valencia, June 9-12)

[pedroza at uma.es]

Dear colleagues,
Apologies for any cross-posting.

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*LAST CALL FOR PAPERS (EXTENDED)*

LODAS 2026 - The 1st International Workshop on Learning and Optimization 
for Distributed AI Systems
Co-located with FLICS 2026 (Valencia, Spain, June 9-12, 2026)

Submission deadline (EXTENDED): *MAY 5, 2026*

Workshop website: https://jamaltoutouh.github.io/lodas2026/
Conference website: https://flics-conference.org/

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SCOPE
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LODAS 2026 brings together researchers working at the intersection
of learning and optimization for distributed AI systems, including edge,
federated, and resource-constrained environments.


Topics of interest include (but are not limited to):

* Federated, distributed, and edge learning
* Communication-efficient and resource-aware AI
* Multi-objective and constrained optimization
* Workflow scheduling and system-level optimization
* Agentic AI and autonomous multi-agent systems
* Foundation models under system constraints
* Trustworthy, privacy-preserving, and robust AI
* Cyber-physical systems, IoT, and digital twins

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SUBMISSION INFORMATION
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Submission via EasyChair (see workshop website)

* Format: IEEE A4 conference template

Paper types:
* Long papers: 7–8 pages
* Short/position papers: 4–6 pages
* Poster papers (undergraduate): 1–2 pages

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IMPORTANT DATES
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* Submission deadline: May 5, 2026 (FINAL EXTENDED)
* Notification: May 10, 2026
* Camera-ready & registration: May 20, 2026
* Workshop: June 9–12, 2026 (exact date TBA)

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ORGANIZING COMMITTEE
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* Jamal Toutouh – Universidad de Málaga, Spain (jamal at uma.es)
* Gabriel Luque – Universidad de Málaga, Spain (gluque at uma.es)
* Diego Daniel Pedroza-Perez – Universidad de Málaga, Spain 
(pedroza at uma.es)

We strongly encourage you to submit your latest work.

We would also appreciate it if you could share this call with interested 
colleagues.

Best regards,
LODAS 2026 Organizing Team

https://jamaltoutouh.github.io/lodas2026/