Elisa Omodei

Elisa Omodei

UN World Food Programme

Elisa Omodei is the Lead Data Scientist of the Hunger Monitoring Unit at the UN World Food Programme’s Research, Assessment and Monitoring division. She also serves as Vice-President Secretary of the Complex Systems Society. She holds a BSc and a MSc in Physics from the University of Padua and Bologna, respectively, and a PhD in Applied Mathematics for the Social Sciences from the École Normale Supérieure of Paris. After her PhD, she spent two years as a postdoctoral researcher at the Rovira and Virgili University in Tarragona, Spain. She then joined the United Nations in 2017, first at UNICEF’s Office of Innovation in New York and now at the World Food Programme in Rome. Elisa is passionate about technological innovation for social good, and in her work she explores how to apply complexity science, data science and AI for development and humanitarian action.

Who, where, why: non-traditional data and predictive analytics to map socio-economic vulnerabilities

In a rapidly changing world, severely affected by extreme weather events, epidemic outbreaks, economic shocks and conflicts, it is of fundamental importance to understand where the most vulnerable people are, how many they are, and to identify what it is that makes them more vulnerable than others to these threats. During the last decade, research has shown that data such as digital traces, phone metadata and satellite imagery carry relevant information beyond their original purpose and can be used as a proxy to measure socio-economic characteristics and detect vulnerabilities when traditional data is not available. Following an overview of these studies, the talk will deep dive into the UN World Food Programme’s original work on predicting food security. We will then conclude by discussing challenges and limitations, but also opportunities, that come with these approaches.