December 5, 2024
09:00-17:00

The field of Machine Learning (ML) for combustion research is rapidly advancing, with the UK playing a pivotal role in integrating ML and combustion science, as demonstrated by the increasing volume of research in this area. Machine Learning for Combustion Meeting is co-organised by research groups from Queen Mary University of London, Imperial College London, and the University of Southampton, and provides a forum to present recent advances in ML for combustion science and engineering in (but not limited to) the following areas:

• ​Combustion Chemistry Acceleration
• Modelling Subgrid Scales in Large-Eddy Simulation
• Flame Diagnostics and Emissions Prediction
• Anomaly Detection
• Fuel Design and Engine Optimisation
• Thermal Runaway Prediction in Li-ion Batteries

The one-day meeting organised under the auspices of Combustion Institute British Section (CIBS) will feature two keynotes and ten invited talks from leading researchers in ML for combustion and wider research community. The event will conclude with a panel discussion involving key stakeholders in the field.
In addition, early career researchers who are interested in presenting their work as a contributed poster are invited to submit an abstract of 200 to 300 words before the 20th of November 2024. Abstracts should be sent as a PDF through email to ml4com2024@gmail.com and the authors of accepted abstracts will be notified by 25th of November 2024.

Queen Mary University of London
London,
UNITED KINGDOM

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Amin Paykani

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