Mohamed Shamroukh
doctoral researcher (Built environment and design; Applied computing; Other information and computing sciences; Machine learning; Data management and data science; Engineering; Geomatic engineering; Civil engineering)
Loughborough, UK.
Mohamed Shamroukh is a doctoral researcher at The Impact Hub, School of Architecture, Building and Civil Engineering, Loughborough University. He specialises in Geospatial Intelligence, GIS, Remote Sensing, Urban Planning, and GeoAI (Geospatial Artificial Intelligence). His PhD research focuses on data-driven modelling, geospatial analysis, and machine learning for pedestrian-friendly urban planning and sustainable city development. Mohamed has extensive expertise in geospatial data science, urban analytics, spatial modelling, Python programming, and geospatial databases. He has conducted research and teaching in GIS, remote sensing, and urban studies, including experience as a research and teaching assistant at South Valley University, Egypt. His projects include WiFi-based pedestrian monitoring, point of interest (POI) analysis, street network, and geospatial data integration.
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Publications
- Building A Model of Planning Criteria for Public Services in Qena City Using Smart Spatial Analysis
- Towards Developing a Web-Based GIS Using Open-Source software: An applied study of public services in Qina City
- Integrating GIS, GeoAI, and Geospatial Programming to Support Methods of Spatial Data Analysis
- Developing a Smart Automated GIS Map for The Public Services in Qena City: An Applied Study in GIS
- QGIS Pip Manager
- Spatio-Temporal analysis of pedestrian activity in Loughborough using WiFi data
- Data-driven prioritising of pedestrian-oriented infrastructure: A framework for resources allocation
- Reliability and scalability of pedestrian monitoring practices: A systematic review
- From Data to Decisions: Understanding Pedestrian Flow with WiFi Scanner Data