Our work advances data-driven, design-based social science at both planetary and household scales. We develop methods at the intersection of causal inference, machine learning, and computational social science; build text-based AI systems; integrate Earth-observation and other high-dimensional data; and create open software and infrastructure. We apply these tools to problems in development, governance, political behavior, and social movements, working across disciplines and geographies. Our work is collaborative, reproducible, and supported by competitive, peer-reviewed funding, outlined below.

[5] Lambda, Inc Research Grant ($7,000, 2026)

[4] Swedish National Space Agency (SNSA) Research Grant (SEK 6,563,000 [USD 696,626]; Chalmers University of Technology, 2025–2028)
• Role: Co-PI (PI: Adel Daoud)
• Project Title: Comparing Earth Observation and AI Methods for Measuring Poverty Towards Sustainable Development

[3] Google Cloud Research Credit Award ($2,500, 2025)

[2] Resnick Sustainability Institute (RSI) Impact Grant ($230,000; Caltech, 2024)
• Role: Co-PI (PI: Hannah Druckenmiller)
• Project Title: New Tools for Estimating Location-specific Ecosystem Values at National Scale to Inform Sustainable Management

[1] OVPR-CoLA Partnership Award ($2,557; UT Austin, 2024)