Susana Constenla-Villoslada

I am a PhD candidate at the I School working at the intersection of econometrics and machine learning for international development. I specialize in causal inference methods for impact evaluation design and implementation, as well as machine-learning-based predictive modeling for cross-sectional and forward-looking applications, including targeting and early warning. My current research focuses on the design and accountable deployment of predictive systems to guide resource allocation in humanitarian aid and social protection programs.

Over the past four years, in close collaboration with partners in the Government of Kenya, I have led the design and implementation of a machine-learning-based early warning system for child malnutrition crises in Kenya’s arid and semi-arid lands (ASAL). As of 2024, nearly 900,000 children under the age of five were estimated to be acutely malnourished in the Kenyan ASAL. The system is designed to detect early signals of localized increases in child wasting and trigger anticipatory action before these trends evolve into sustained periods of elevated child malnutrition at the community level.

Prior to joining the I School, I spent three years as a Research Analyst at the International Food Policy Research Institute (IFPRI) in Washington, D.C. I hold an M.S. in Development Economics from Cornell University, earned under a Fulbright Scholarship, and a B.S. with honors in Agricultural Engineering from the Polytechnic University of Madrid.

Publications:

Constenla-Villoslada, S., Liu, Y.,  McBride, L.,  Ouma, C.,  Mutanda, N., & Barrett, C.B. (2025). High-frequency monitoring enables machine learning–based forecasting of acute child malnutrition for early warning, PNAS. U.S.A. 122 (23) e2416161122, https://doi.org/10.1073/pnas.2416161122.

Constenla-Villoslada, S., Liu, Y., Wen, J. et al. (2022). Large-scale land restoration improved drought resilience in Ethiopia’s degraded watersheds. Nature Sustainability. https://doi.org/10.1038.

Upton, J., Constenla-Villoslada, S. and Barrett, C.B. (2022). “Caveat utilitor: A comparative assessment of resilience measurement approaches”, Journal of Development Economics, Vol- 157, 102873.https://doi.org/10.1016/j.jdeveco.2022.102873.