[Academic Website]
Dani Arribas-Bel is interested in computers, cities, and data. He is Professor in Geographic Data Science at the the University of Liverpool, and Deputy Programme Director for Urban Analytics at the Alan Turing Institute, where he was also ESRC Fellow from 2020 to 2023. Prior to arriving at Liverpool in 2015, Dani held positions at the University of Birmingham (UK), the VU University in Amsterdam (Netherlands), Arizona State University (US), and Universidad de Zaragoza (Spain). He holds honorary positions at the University of Chicago's Center for Spatial Data Science, and the Center for Open Geographical Science of San Diego State University. Dani's research combines modern computation with new forms of data to shed light on the spatial structure(s) of cities. His research is published in journals such as PLOS ONE, Demography, Geographical Analysis, or Environment and Planning (A/B/C). Together with Serge Rey and Levi Wolf, he is the author of "Geographic Data Science with Python", published by CRC Press in 2023. Dani currently serves as co-editor of the journal "Environment and Planning B - Urban Analytics & City Science”, where he co-founded the Urban Data/Code section.
Dani Arribas-Bel is interested in computers, cities, and data. He is Professor in Geographic Data Science at the Department of Geography and Planning of the University of Liverpool, where he is a member of the Geographic Data Science Lab. He is the Deputy Programme Director for Urban Analytics at The Alan Turing Institute, where he was also an ESRC Fellow from 2020-23. Prior to his appointment in 2022, Dani was Lecturer and Senior Lecturer in Geographic Data Science at the University of Liverpool, lecturer in Human Geography at the University of Birmingham (UK), postdoctoral researcher at the VU University in Amsterdam (Netherlands), postdoctoral research associate at Arizona State University’s GeoDa Center for Geospatial Analysis and Computation (US), and PhD student at Universidad de Zaragoza (Spain).
Dani's research combines modern computation and new forms of data to understand cities. His substantive interests focus on the spatial dimensions of cities and how urban activites unfold over space and time. Methodologically, he is at the forefront of efforts arguing for tighter integration between geography and data science, and works to leverage recent technologies that generate new data such as high-resolution satellite imagery or digital footprint data. He has published more than 50 articles in journals such as PLoS ONE, Demography, the Annals of the American Association of Geographers, or Environment and Planning (A/B/C). He is committed to open science and interdisciplinary collaboration. Dani has been a member of the development team of PySAL, the Python library for spatial analysis, since its first release in 2009; has created the Python library contextily, which enables access to web tiles; and has participated as mentor in three Google Summer of Code programmes. Together with Serge Rey and Levi Wolf, he is the author of the book "Geographic Data Science in Python", published by CRC Press in 2023.
Dani has been invited to give talks at universities around the world, including India, Japan, Brazil, or Colombia. He holds honorary positions at the University of Chicago's Center for Spatial Data Science and the Center for Open Geographical Science of San Diego State University, and he is a member of the OECD's Geospatial Data Lab, where he coordinates a workstream on Urban Analytics. Dani currently serves as co-editor of the journal “Environment and Planning B - Urban Analytics & City Science”, where he co-founded the Urban Data/Code section and, from 2020 to 2024, he was associate editor at the "Journal of the Royal Statistical Society Series A - Statistics in Society". He is member of the editorial board of Spatial Economic Analysis, Geographical Analysis, and Journal of Geographical Systems. From 2017 to 2022, he chaired the Quantitative Methods Research Group of the Royal Geographical Society.
