Technical Conference: 15 - 19 March 2026
Exhibition: 17 - 19 March 2026
Los Angeles Convention Center | Los Angeles, California, United States

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Technical Conference: 15 - 19 March 2026
Exhibition: 17 - 19 March 2026
Los Angeles Convention Center | Los Angeles, California, United States

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Machine Learning Challenge Submission Guidelines

 
Organizers

Tingjun Chen, Duke University, USA
Dan Kilper, Trinity College Dublin, Ireland
Camille Delezoide, Nokia Bell Labs, France

Background, Motivation, and Objective

In recent years, machine learning (ML) has proven to be a transformative tool in modeling and understanding complex real-world data and systems. Its applications have revolutionized fields such as natural language processing, image processing, and radio frequency (RF) systems. In addition to contributions from industry and academia, the scientific advances in these fields have also been driven in part by challenges organized by the broader community, leveraging large-scale datasets such as MNIST, ImageNet, and RF signal classification. Recent breakthroughs have also shown the potential of using ML to improve modeling, performance prediction, and resource provisioning in optical networks across various scales. However, despite the growing number of works, the field still lacks, to the best of our knowledge, universal benchmarks with structured datasets to guide the community in pushing forward the frontier in this research direction.

We are proud to anounce the first OFC 2026 ML Challenge. For more information including objectives, timeline, prizes, materials, and submission instructions, please visit the ML Challenge page.

Call for Submission

Detailed submission guidelines for the OFC 2026 ML Challenge.

Important Dates
  • Competition launch with dataset and instructions release: Dec. 1, 2025
  • Submission deadline: Jan. 30, 2026
  • Finalists announced: Feb. 15, 2026
  • Live competition and winners announced: During OFC 2026 (Mar. 15–19)
Award
  • Invited papers from the ML Challenge winner to the IEEE/Optica Journal of Optical Communications and Networking(JOCN)
  • A dedicated repository for hosting all the ML Challenge results and the leaderboard
Submission Details

How to Participate

  1. Download the challenge data for the different challenge tracks indicated in each track.
  2. Run your model to obtain predictions for each task included in the challenge track
  3. [optional] Verify your model performance before submitting
    1. Create an account on kaggle platform.
    2. Upload your results on the Kaggle submission platform for the validation.
  4. To be eligible for the awards, you must submit a report to ofc.ml.challenge@gmail.com, describing the model you used to obtain the prediction, upload and public your model/runnable code on the github, and attach the predicted CSV file.
Evaluation Metrics
  • 60 credits: 20 credit per testcase results
  • 30 credits: 1-2 page report (overleaf template) in terms of novelty, innovations, and clarity
  • 10 credits: artifact for rerun the model
Questions?

If you have any questions about the submission process, please contact:

Email: ofc.ml.challenge@gmail.com or zehao.w@duke.edu