Hadi joined WorldPop as a Research Fellow in October 2026. He is a geospatial data scientist with a background in Earth observation, remote sensing, spatial analysis and large-scale geospatial data processing. He holds a D.Sc. in Geoinformatics from Aalto University and has previously worked at IIASA, the University of Bonn and in the private sector. His research combines satellite observations, statistical and machine-learning methods, and socioeconomic data to investigate land-cover change, agricultural productivity, land degradation and environmental risks. He has also contributed to policy-oriented research with FAO and the World Bank, including global assessments integrating satellite-derived environmental data with population and vulnerability datasets.

At WorldPop, Hadi will contribute to the development of geospatial methods and computational workflows for high-resolution population mapping, such as the development of annual settlement covariates for global high-resolution population mapping. His broader research interests include integrating emerging satellite- and AI-derived geospatial datasets into population modelling, developing scalable and reproducible computational workflows, and improving the evaluation and uncertainty quantification of gridded population estimates. He is also interested in applying population data to understand human exposure and vulnerability to environmental and climate-related hazards, particularly in data-poor settings.