2026: Leveraging AI and Forecast Models for Anticipatory Action Response Analysis To Reduce Acute Child Malnutrition (IFPRI)
Through this collaboration between Cornell Atkinson and the Cornell Joan Klein Jacobs Center for Precision Nutrition and Health, this project addresses acute child malnutrition as a climate-sensitive threat by bridging the gap between advanced forecasting and effective humanitarian response. Building on machine-learning models that predict malnutrition risk months in advance, the project will design the scientific and technical foundations of an AI-enabled response analysis system. The system will integrate climate-informed forecasts with curated evidence on nutrition, cost-effectiveness, and operational feasibility to guide anticipatory action. Seed funding will support a Nairobi-based stakeholder workshop to define priority use cases, evidence requirements, system architecture, and safeguards, enabling future climate-resilient, timely, and cost-effective responses in high-risk settings across Kenya’s arid regions globally.
Cornell: Chris Barrett (Dyson School), Aditya Vashistha (Cornell Bowers), Julia Finkelstein (Human Ecology/Nutritional Sciences), Elizabeth Tennant (Dyson School)
International Food Policy Research Institute (IFPRI): Rebecca Brander (Nairobi)