معرفی
Dr. S.M. Labib is an Assistant Professor at Utrecht University's Faculty of Geosciences, within the Department of Human Geography and Spatial Planning. He also holds a visiting role as a Research Associate at the University of Cambridge. His work focuses on urban health, environmental exposures, and sustainable cities, combining geospatial methods with data science and machine learning. Labib actively promotes open science and FAIR data principles through collaborative interdisciplinary research.
Education:
- PhD in Geography, University of Manchester (2020)
- MSc in Geographical Information Science, University of Manchester (2017)
- Summer School on Data Science and Big Data Analytics, London School of Economics (2017)
- Bachelor of Urban and Regional Planning, Bangladesh University of Engineering and Technology (2014)
Research Interests: Labib’s research addresses public health challenges in urban environments, emphasizing spatial and societal disparities. He explores three core tracks:
(1) Urban health dynamics in global North/South contexts,
(2) Geographical methods/tool development for health impact modeling,
(3) AI-driven analysis of environmental and social health factors using novel datasets. His work bridges health geography, urban planning, and environmental epidemiology.
Teaching & Advising: Coordinates the undergraduate Health Geography course and co-coordinates Spatial Statistics and Machine Learning in the Applied Data Science Master program. He employs active and problem-based learning strategies. Currently supervises 2 PhD students and 2 postdocs, with over 10+ MSc students supervised previously. Expresses openness to mentoring future PhD candidates aligned with his research themes.
Grants & Projects: Leads the ECO-MIND project (2023–2027) on nature exposure and youth mental health funded by Utrecht University. Collaborates on the UPSCALE project (2024–2027) investigating health technology transitions, supported by an NWO grant. Previously developed the An image tells more than a thousand words project (2023–2024), analyzing streetscapes via AI and crowdsourced data.
Labs & Teams: Director of the Spatial Data Science and Geo-Intelligence (SDGI) Lab, which produces open-source toolkits like R-packages and Python libraries. Collaborates globally with researchers through the Utrecht Exposome Hub and Pathways to Sustainability initiative.
