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Head of the Department of Human Geography, Lund University

I am a senior lecturer, reader and department head. My research bridges the gap between technical and social sciences, with time spent at institutions like MIT and the Royal Institute of Technology. My work primarily focuses on using satellite data, such as nighttime lights, to analyze economic development in areas with limited statistical data. This approach is particularly impactful in regions with underdeveloped public statistics or restrictive regimes.

I am is also the co-author of "Models for Non-Modelers," a guide for social scientists and researchers in understanding and applying data and statistical models. This work simplifies complex concepts in AI, epidemiology, and climate science, making them accessible to those without extensive mathematical backgrounds.

Recently, I have focused on the use of AI and satellite imagery in poverty analysis. Research in this field involves statistical analysis of welfare and poverty predictions, emphasizing the synergy of machine learning and deep learning in enhancing predictive accuracy. Recently, I combine high-resolution satellite imagery with expert analysis to estimate welfare levels, using the 2015 Tanzania DHS dataset for validation. This innovative approach highlights the potential of integrating human expertise with AI in socioeconomic research.
My mark is to merge technical and social science disciplines, making significant strides in GIS applications for socioeconomic studies and advancing the use of AI and satellite imagery in understanding complex global issues.


  • –present
    Lecturer in Geography, Lund University


  • 2003 
    Stockholm university, PhD/Human geography