[hpc-announce] [CFP] LODAS 2026 – Learning & Optimization for Distributed AI Systems @ FLICS 2026 (June 9–12, Valencia)

[Diego Pedroza]

(Apologies for any cross-posting).

Dear colleagues,

We are pleased to invite submissions to:

LODAS 2026 – The 1st International Workshop on Learning and Optimization 
for Distributed AI Systems <https://urldefense.us/v3/__https://jamaltoutouh.github.io/lodas2026/__;!!G_uCfscf7eWS!ey5gXmx5b2Fe173EW7NK9dlzEfbWpKWhrhxrpafZcYQwl75hvYW3EVbQf_vxBsKNk624VUMniL5hwydEd7mhCQ$ >. 
Co-located with FLICS 2026 <https://urldefense.us/v3/__https://flics-conference.org/__;!!G_uCfscf7eWS!ey5gXmx5b2Fe173EW7NK9dlzEfbWpKWhrhxrpafZcYQwl75hvYW3EVbQf_vxBsKNk624VUMniL5hwyf2CGPmqw$ >Valencia, 
Spain. June 9–12, 2026.

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    Workshop
    website:<https://urldefense.us/v3/__https://jamaltoutouh.github.io/lodas2026/?utm_source=chatgpt.com__;!!G_uCfscf7eWS!ey5gXmx5b2Fe173EW7NK9dlzEfbWpKWhrhxrpafZcYQwl75hvYW3EVbQf_vxBsKNk624VUMniL5hwyfNUKIoBQ$ >https://urldefense.us/v3/__https://jamaltoutouh.github.io/lodas2026/__;!!G_uCfscf7eWS!ey5gXmx5b2Fe173EW7NK9dlzEfbWpKWhrhxrpafZcYQwl75hvYW3EVbQf_vxBsKNk624VUMniL5hwydEd7mhCQ$ 
    <https://urldefense.us/v3/__https://jamaltoutouh.github.io/lodas2026/__;!!G_uCfscf7eWS!ey5gXmx5b2Fe173EW7NK9dlzEfbWpKWhrhxrpafZcYQwl75hvYW3EVbQf_vxBsKNk624VUMniL5hwydEd7mhCQ$ >

  *

    Conference website:https://urldefense.us/v3/__https://flics-conference.org/__;!!G_uCfscf7eWS!ey5gXmx5b2Fe173EW7NK9dlzEfbWpKWhrhxrpafZcYQwl75hvYW3EVbQf_vxBsKNk624VUMniL5hwyf2CGPmqw$ 
    <https://urldefense.us/v3/__https://flics-conference.org/?utm_source=chatgpt.com__;!!G_uCfscf7eWS!ey5gXmx5b2Fe173EW7NK9dlzEfbWpKWhrhxrpafZcYQwl75hvYW3EVbQf_vxBsKNk624VUMniL5hwyfeDF5Mlg$ >


    Scope

Modern AI systems must operate under real-world constraints: distributed 
data ownership, limited communication, resource limitations, privacy 
requirements, latency bounds, dynamic environments, and heterogeneous 
devices.

LODAS 2026focuses on the intersection of:

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    Machine Learning

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    Evolutionary Computation

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    Distributed/Federated Learning

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    Optimization & Scheduling

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    AI Systems & Deployment

We aim to bridge learning algorithms and system-level design, promoting 
research where models, optimization strategies, and infrastructures are 
co-designed for scalable, reliable, and efficient distributed AI systems.

We welcome both theoretical and applied contributions, including 
empirical studies, benchmarks, simulations, and real-world deployments.

Topics of interest (non-exhaustive)

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    Federated, distributed, and edge learning

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    Communication-efficient and resource-aware AI

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    Multi-objective and constrained optimization

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    Workflow scheduling and system-level optimization

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    Agentic AI and autonomous multi-agent systems

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    Foundation models under system constraints

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    Trustworthy, privacy-preserving, and robust AI

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    Cyber-physical systems, IoT, and digital twins

Submissions

Submitted papers (PDF) must use the A4 IEEE Manuscript Templates for 
Conference Proceedings and must include keywords.

Submission types:

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    Long papers: 7–8 pages (research contributions)

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    Short / position papers: 4–6 pages (work-in-progress, visionary ideas)

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    Poster papers (undergraduate): 1–2 pages

All submissions must comply with the FLICS 2026 Submission Instructions 
and be submitted via EasyChair.

Important dates

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    *Submission deadline: April 21, 2026*

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    Acceptance notification: May 5, 2026

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    Camera-ready & registration: May 15, 2026

Workshop dates: June 9–12, 2026 (exact day/time to be announced in the 
FLICS program)

Organizers

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    Jamal Toutouh, University of Málaga, Spain (jamal at uma.es)

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    Gabriel Luque, University of Málaga, Spain (gluque at uma.es)

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    Diego Daniel Pedroza-Perez, University of Málaga, Spain (pedroza at uma.es)


We warmly encourage you to submit your work and to forward this CFP to 
colleagues and relevant mailing lists.

Best regards,

LODAS 2026 Workshop Organizing Team