The AI & Global Development Lab advances a planetary-scale, causal atlas of human development by fusing Earth-observation imagery, machine learning, and rigorous inference to map poverty dynamics and evaluate policy impacts across time and space. Our work is made possible by competitive, peer-reviewed support.

[8] Swedish National Space Agency (SNSA) Research Grant (2025, 6.5 million SEK [USD 696,626]) – Comparing Earth Observation and AI Methods for Measuring Poverty Towards Sustainable Development.

[7] Chalmers Innovation Office (2023, 0.1 million SEK [0.01 million USD]) – Seed funding to evaluate the utilization potential of AI and Earth Observation for the Aid Industry.

[6] The Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (2022, 6 million SEK [0.6 million USD]) – Countering Bias in AI Methods in the Social Sciences; for Advanced Networking Excellence Between Universities and External Partners (with Richard Johansson and Moa Johansson).

[5] EU Horizon Grant (2022, 3.5 million SEK [0.35 million USD]) – Towards a sustainable wellbeing economy: integrated policies and transformative indicators.

[4] Swedish Research Council’s Research Environment Grant (2020; 18 million SEK [1.8 million USD]) – Combining satellite images and artificial intelligence to measure poverty in 1982-2020, and use these data to explain the effects of World Bank and Chinese development programs in Africa. Awarded to only about 8 projects in the social sciences. Acceptance rate 7 percent.

[3] Swedish Research Council’s Consolidator Grant (2020; 12 million SEK [1.2 million USD]) – Observatory of poverty: Combining image-recognition algorithms and satellite images to produce historical and geographical poverty data of Africa

[2] Chalmers AI Research Centre Seed Grant 0.3 million SEK (30 000 USD) – Observatory of poverty—Harnessing machine intelligence to detect African poverty and inequality from satellite images. Awarded to only about 20 projects across natural, medical and social sciences every second year. Acceptance rate 7 percent.

[1] Swedish Research Council’s Register-based Research (13 million SEK [1.3 million USD]) – Understanding society through register-based machine learning. Acceptance rate 18%.