Ed’s research aims to deepen our quantitative understanding of human behaviour in cities, and how these behaviours shape urban activity and dynamics. He is particularly interested in the role of bounded rationality and spatial cognition in travel decision-making, and the adaptation of behaviour in response to short and long-term shocks. His research combines quantitative methods, including exploratory data analysis, machine learning, agent-based modelling, and network modelling, with theory drawn from diverse disciplines such as urban geography, transportation, spatial cognition, judgment and decision-making, and sociology. He also has interests in the role of data visualisation in communicating complex datasets for decision-making.