posted by user: pedroza || 25 views || tracked by 1 users: [display]

LODAS 2026 : International Workshop on Learning and Optimization for Distributed AI Systems.

FacebookTwitterLinkedInGoogle

Link: https://jamaltoutouh.github.io/lodas2026/
 
When Jun 9, 2026 - Jun 12, 2026
Where Valencia, Spain
Submission Deadline Apr 21, 2026
Notification Due May 5, 2026
Final Version Due May 15, 2026
Categories    machine learning   evolutionary computation   optimization & scheduling   ai systems & deployment
 

Call For Papers

We are pleased to invite submissions to:

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.

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

# 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 2026 focuses on the intersection of:
* Machine Learning
* Evolutionary Computation
* Distributed/Federated Learning
* Optimization & Scheduling
* 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)

* 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

# Submissions

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

## Submission types:


* Long papers: 7–8 pages (research contributions)
* Short / position papers: 4–6 pages (work-in-progress, visionary ideas)
* Poster papers (undergraduate): 1–2 pages

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

## Important dates

* Submission deadline: April 21, 2026
* Acceptance notification: May 5, 2026
* Camera-ready & registration: May 15, 2026

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

## Organizers

* Jamal Toutouh, University of Málaga, Spain (jamal@uma.es)
* Gabriel Luque, University of Málaga, Spain (gluque@uma.es)
* Diego Daniel Pedroza-Perez, University of Málaga, Spain (pedroza@uma.es)

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

Related Resources

Learning & Optimization 2026   ASCE EMI Minisymposium on Probabilistic Learning, Stochastic Optimization, and Digital Twins
Ei/Scopus-ITCC 2026   2026 6th International Conference on Information Technology and Cloud Computing (ITCC 2026)
DMO-FinTech 2026   2nd International Workshop on Decision-Making and Optimization in Financial Technologies
AMLDS 2026   IEEE--2026 2nd International Conference on Advanced Machine Learning and Data Science
AI-EE 2026   2026 International Conference on Artificial Intelligence and Electrical Engineering-EI/Scopus
Ei/Scopus-CMLDS 2026   2026 3rd International Conference on Computing, Machine Learning and Data Science (CMLDS 2026)
AIETA 2026   2026 International Conference on AI in Education Technology and Applications-EI/Scopus
CVIPPR 2026   2026 4th Asia Conference on Computer Vision, Image Processing and Pattern Recognition (CVIPPR 2026)
AIACT 2027   2027 11th International Conference on Artificial Intelligence, Automation and Control Technologies
CACML 2026   2026 5th Asia Conference on Algorithms, Computing and Machine Learning (CACML 2026)