Scholar
SM Labib
Google Scholar ID: MPc35dkAAAAJ
Assistant Professor, Utrecht University
Citations & Impact
Citations
2,248
H-index
20
i10-index
27
Publications
20
Co-authors
42
list available
Publications
Resume (English only)
Academic Achievements
- Published diverse scientific articles in various reputed journals and conferences and presented his work as invited talks. Created several open-source data analysis toolkits as part of his research lab 'Spatial Data Science and Geo-Intelligence' outputs (e.g., R-package, Python toolkits). Currently supervising or co-supervising two PhD students and two postdocs.
Research Experience
- Current research focuses on three tracks: (i) Exploring public health in diverse urban contexts encompassing cities in the global north and south; (ii) Developing and applying geographical methods and tools in studying health and modeling health impacts; (iii) Integrating data-driven methods and artificial intelligence models (e.g., Deep learning - image analysis, machine learning) in studying complex environmental, and social aspects of health using new forms of data.
Background
- Areas of expertise include Data Science, Geographic Information Science, Spatial Analysis, Geocomputation, and Machine Learning. His primary research revolves around understanding and predicting public health concerns in urban contexts from the viewpoint of environmental exposures, urban planning, and health system perspectives by applying diverse methodological approaches, including quantitative geographical information science, data science, and health impact assessment.
Miscellany
- Teaching holds a pivotal role in his academic journey. He enjoys engaging with diverse students from various backgrounds at different levels of study. Coordinates undergraduate Health Geography course and co-coordinates Spatial statistics and machine learning courses in the applied data science master program.
