2026: Data Science to Build Resilience and Improve Humanitarian Response (UNHCR, WFP)
This project will gather leading researchers and policy experts to explore how data science advances can strengthen responses to climate emergencies and food security crises. The summit will examine three key areas: creating better data systems in regions with limited information, improving prediction models using machine learning, and designing early warning systems that help organizations make faster decisions during humanitarian emergencies. Representatives from international organizations, development banks, and research institutions will participate in discussions that bridge the gap between technical innovation and real-world disaster response. The project will produce a comprehensive white paper identifying research priorities and opportunities for future collaboration. By connecting data science capabilities with humanitarian needs, this initiative aims to improve decision-making and resource allocation during climate-related disasters, ultimately helping vulnerable communities prepare for and respond to environmental threats more effectively.
Cornell: Christopher Barrett (Cornell SC Johnson College of Business/Dyson School of Applied Economics and Management)
UN World Food Programme (WFP): Kyriacos Kouppari (Head of Hunger Monitoring Unit)
UN Refugee Agency (UNHCR): Rebeca Moreno Jimenez (Lead Data Scientist)