Team
An interdisciplinary team spanning computer science, statistics, political science, and sociology.
Lab Directors
Connor T. Jerzak
Assistant Professor, Department of Government
UT Austin
Research focuses on causal inference methodology, AI applications to global development challenges, and text-based AI systems.
Adel Daoud
Associate Professor, Institute for Analytical Sociology
Linköping University / Chalmers University
Research focuses on AI/ML applications for poverty analysis, satellite imagery interpretation, and causal inference methods.
Xiao-Li Meng
Whipple V. N. Jones Professor of Statistics
Harvard University
Founding Editor-in-Chief of Harvard Data Science Review. Former Dean of Harvard Graduate School of Arts and Sciences (2012-2017).
Researchers
Fredrik D. Johansson
Associate Professor, Machine Learning
Chalmers University of Technology
PI of the Healthy AI Lab; research on causal inference and decision-making with applications in healthcare.
Devdatt Dubhashi
Head of Unit, Data Science and AI
Chalmers University of Technology
Research on randomized algorithms and machine learning for big data.
James H. Bailie
Postdoc – Statistician
Chalmers University of Technology
Postdoc in Data Science and AI; works on statistical methods for global development.
Mohammad Kakooei
Postdoctoral Researcher
Chalmers University of Technology
Research on image processing, machine learning, and remote sensing.
Satiyabooshan Murugaboopathy
Researcher
Linköping University
Institute for Analytical Sociology (IAS).
Students
Ph.D.
Markus Pettersson
PhD Student, Data Science and AI (CSE)
Chalmers University of Technology
Joint work: Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: One Map, Many Trials in Satellite-Driven Poverty Analysis.
Master’s
Mishu Dhar
Master's Student, Computational Social Science (Ongoing)
Linköping University
Mattias Antar
Master's Student, Computational Social Science (Defended 2026)
Linköping University
Thesis: Temporal Dynamics of Development Aid in Africa: A Difference-in-Differences Study.
Cindy Conlin
Master's Student, Computational Social Science (Defended 2024)
Linköping University
Thesis: Using Machine Learning and Daytime Satellite Imagery to Estimate Aid’s Effect on Wealth: Comparing China and World Bank Programs in Africa.
Mikael P. Gustafsson
Master's Student, Computational Social Science (Defended 2024)
Linköping University
Thesis: Estimating Aid Effectiveness in Fragile and Conflict-affected States: Evidence from Satellite-based Inference in Somalia.
