Stef De Sabbata

Stef De Sabbata

Associate Professor of Geographical Information Science

University of Leicester

Biography

Hi there 👋 😊 my name is Stef and I am an Associate Professor of Geographical Information Science at the School of Geography, Geology and the Environment and Research Theme Lead for Cultural Informatics at the Institute for Digital Culture of the University of Leicester. I am the Chair of the Geographic Information Science Research Group of the Royal Geographical Society with IBG. I am also part of the steering committee of GIScience Research UK (GISRUK), and I was the chair of the GISRUK 2018 conference. I am a member of the Commission on Location Based Services of the International Cartographic Association.

Before joining the University of Leicester in 2015, I was a Researcher at the Oxford Internet Institute of the University of Oxford (2013-2015) and a Junior Research Fellow at the Wolfson College of the University of Oxford (2014-2015), and thereafter, a Research Associate of the Oxford Internet Institute of the University of Oxford (2015-2021). I was awarded a PhD from the Department of Geography of the University of Zurich in 2013 and a BSc and a MSc in computer science from the Department of Mathematics and Computer Science of the University of Udine.

Interests
  • Artificial Intelligence
  • Data Science
  • Digital Geographies
  • Environmental Sustainability
  • Geographic Information Science
  • Urban Geography
Education

  • PhD in Geographic Information Science, 2013

    University of Zurich

  • MSc in Computer Science, 2008

    University of Udine

  • BSc in Computer Science, 2005

    University of Udine

Selected Publications

De Sabbata, S. and Liu, P. (2023). A graph neural network framework for spatial geodemographic classification. International Journal of Geographical Information Science, 37(12), 2464-2486, 2464-2486, DOI: 10.1080/13658816.2023.2254382

De Sabbata, S. et al. (2023). GeoAI in urban analytics. International Journal of Geographical Information Science, 37(12), 2455-2463, DOI: 10.1080/13658816.2023.2279978

De Sabbata, Stefano, Andrea Ballatore, Pengyuan Liu, and Nicholas J. Tate. (2023). Learning Urban Form Through Unsupervised Graph-Convolutional Neural Networks. In The 2nd International Workshop on Geospatial Knowledge Graphs and GeoAI: Methods, Models, and Resources, September 12th, 2023. Leeds, UK.

Bennett, K. and De Sabbata, S. (2023). Introducing a more-than-quantitative approach to explore emerging structures of feeling in the everyday. Emotion, Space and Society, 49, p.100965.

Liu, P., & De Sabbata, S. (2021). A graph-based semi-supervised approach to classification learning in digital geographies. Computers, Environment and Urban Systems, 86, 101583.

Ballatore, A., & De Sabbata, S. (2020). Los Angeles as a digital place: The geographies of user‐generated content. Transactions in GIS, 24(4), 880-902.

Gardner, Z., Mooney, P., De Sabbata, S., & Dowthwaite, L. (2020). Quantifying gendered participation in OpenStreetMap: responding to theories of female (under) representation in crowdsourced mapping. GeoJournal, 85(6), 1603-1620.

De Sabbata, S., & Liu, P. (2019). Deep learning geodemographics with autoencoders and geographic convolution. In Proceedings of the 22nd AGILE conference on Geographic Information Science, Limassol, Greece.

Bright, J., De Sabbata, S., Lee, S., Ganesh, B., & Humphreys, D. K. (2018). OpenStreetMap data for alcohol research: Reliability assessment and quality indicators. Health & place, 50, 130-136.

Acheson, E., De Sabbata, S., & Purves, R. S. (2017). A quantitative analysis of global gazetteers: Patterns of coverage for common feature types. Computers, Environment and Urban Systems, 64, 309-320.

Reichenbacher, T., De Sabbata, S., Purves, R. S., & Fabrikant, S. I. (2016). Assessing geographic relevance for mobile search: A computational model and its validation via crowdsourcing. Journal of the Association for Information Science and Technology, 67(11), 2620-2634.

Graham, M., De Sabbata, S., & Zook, M. A. (2015). Towards a study of information geographies:(im) mutable augmentations and a mapping of the geographies of information. Geo: Geography and environment, 2(1), 88-105.

De Sabbata, S., & Reichenbacher, T. (2012). Criteria of geographic relevance: an experimental study. International Journal of Geographical Information Science, 26(8), 1495-1520.

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