Nii’s research examines how urban transformation can be understood and managed in response to persistent socio-spatial disparities, informality, and environmental change. His work sits at the intersection of GeoAI, critical urban theory, and climate-impact studies, with a regional focus on cities in Ghana and the United States. He employs a mixed-methods approach that integrates computer vision, remote sensing, and spatial statistics with qualitative methods such as interviews, focus groups, and discourse analysis to analyze the spatial and political dimensions of urban development.

His current project uses computer vision models to analyze Google Street View imagery and detect patterns of gentrification in Philadelphia.

More broadly, Nii’s research investigates informal settlement dynamics, the intensity and distribution of urban development, and the spatial consequences of planning and infrastructure under conditions of climate stress. By combining machine learning and spatial analysis with grounded qualitative inquiry, his work aims to bridge technical and critical approaches to studying urban disparities and transformation in the Global South and beyond.

Faculty Advisor: Hamil Pearsall