The Data Learning group is an interdisciplinary group developing pioneering research on fundamental Data Science and Machine Learning for real world applications.

The DataLearning Group uses digital twins and data assimilation to model real-world observations, with machine learning used to increase the reliability of predictions made by forecasting models. The group's work has applications including urban air pollution, medical image segmentation, fluid dynamics and wildfire prediction.