Organising Committee:
Amin Paykani (QMUL)
Stelios Rigopoulos (ICL)
Temistocle Grenga (Soton)
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
· High Fidelity 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 the wider research community. The CIBS AGM meeting will be held during the lunch break. The event will conclude with a panel discussion involving key stakeholders in the field.
Professor
INSA de Rouen Normandie
Professor
University of Cambridge
Imperial College London
University of Southampton
University of Edinburgh
University of Kent
Queen Mary University of London
University of Oxford
Queen Mary University of London
Otto von Guericke University Magdeburg
Imperial College London
University of Derby
ETH Zurich