James' research interests lie in spatio-temporal modelling and analytics, in particular applications of machine learning, deep learning and computer vision to the geoinformation sciences. He has carried out most of his work in the fields of transport and mobility, with applications in travel time forecasting, travel mode and activity detection, and bicycle flow modelling. His current work focuses on using computer vision to sense features of the urban environment for applications including road safety and context detection.