Dani Arribas-Bel is Deputy Director of Urban Analytics at the Turing, and senior lecturer in Geographic Data Science at the Department of Geography and Planning of the University of Liverpool. Prior to his appointment in 2015, he held positions at the University of Birmingham, the VU University in Amsterdam, Arizona State University, and University of Zaragoza. He holds honorary positions at the University of Chicago's Center for Spatial Data Science, the Center for Geospatial Sciences of the University of California Riverside, and the Smart Cities Chair of University of Barcelona.
His research combines urban studies, computational methods and new forms of data, and has been published in journals such as PLOS ONE, Journal of Urban Economics, Demography, Geographical Analysis, or Environment and Planning (A/B/C). He is member of the development team of PySAL, the Python library for spatial analysis, currently serves as co-editor of the journal "Environment and Planning B - Urban Analytics & City Science” and the "Journal of the Royal Statistical Society Series A - Statistics in Society”, and chairs the Quantitative Methods Research Group of the Royal Geographical Society.
Dani is interested in how data science and AI can help us better understand cities and their evolution. His main research integrates new forms of data and methods with traditional spatial analysis and modelling to create representations of the spatial structure of cities. At the Turing, he is focused on using AI and machine learning to leverage satellite imagery, creating high-resolution descriptions of cities that can be updated as new streams of images become available.