AI-Task Team Workshop of OceanPredict - Montreal, 13-14 April 2026 - CALL for ABSTRACTS extended to 2 Jan 2026
Rachel Furner
Dear all,
We are extending the abstract submission period for the AI-TT workshop in Montréal, Canada on the 13+14 April 2026 to the 2nd Jan 2026.
To submit an abstract please follow this link.
Information about workshop objectives, important dates and format can be found on the workshop webpages.
If you have any questions please let us know.
All the best,
The AI-TT organising committee
Sent by the OP programme office
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Kirsten Wilmer-Becker
OceanPredict Programme Coordinator
Met Office, FitzRoy Road, Exeter, EX1 3PB, United Kingdom
Phone: +44 330 135 0000
Please note that I now only work Tuesdays, Wednesday and Thursdays.
My pronouns are she/her/hers.
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Subject: Re: AI-TT Workshop of OceanPredict - Montreal, 13-14 April 2026 - CALL for ABSTRACTS now OPEN
OceanPredict is pleased to invite abstracts to the first workshop of the Artificial Intelligence Task Team (AI-TT) which will focus on “Machine Learning for Ocean Prediction: Methods, Applications & Challenges”.
The workshop will take place at the University of Montréal in collaboration with Environment and Climate Change Canada (ECCC) on the 13th & 14th April 2026.
Abstract submission is now OPEN.
To submit an abstract please follow this link.
The deadline for submissions is Friday, 12 December 2025, 13 UTC.
The workshop will address:
· Machine Learning Emulators: Design, development, and application of machine learning, including generative approaches, as fast, surrogate models for complex ocean processes
· Hybrid Approaches: Integration of physics-based ocean models and machine learning techniques to enhance predictive accuracy and efficiency, e.g. use of ML components (parameterisations, etc) in state-of-the-art physical ocean models, and combining physics and deep learning within in a single differentiable programming framework
· Deep Learning for Data Assimilation, and inversion schemes: Innovative uses of deep learning architectures to assimilate diverse oceanographic datasets, including satellite and in-situ observations. Use of ML for ocean state estimation and forecasting.
· Evaluation Challenges: Strategies and benchmarks for assessing the performance, robustness, and reliability of deep learning-based emulators in operational settings.
· Technical challenges: Operationalization, Novel architectures, Managing and sharing large datasets, etc.
· Other relevant ML applications for Ocean prediction (e.g. downscaling applications, ensemble forecasting)
We will open the full workshop registration in January 2026.
Information about workshop objectives, important dates and format can be found on the workshop webpages.
If you have any questions please let us know.
All the best,
The AI-TT organising committee
Sent by the OP programme office
………………………………………………………………………………………………………………
Kirsten Wilmer-Becker
OceanPredict Programme Coordinator
Met Office, FitzRoy Road, Exeter, EX1 3PB, United Kingdom
Phone: +44 330 135 0000
Please note that I now only work Tuesdays, Wednesday and Thursdays.
My pronouns are she/her/hers.
………………………………………………………………………………………………………………