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Who we are

With research staff from more than 60 countries, and offices across the globe, IFPRI provides research-based policy solutions to sustainably reduce poverty and end hunger and malnutrition in developing countries.

Lina Alaaeldin Abdelfattah

Lina Alaaeldin Abdelfattah is a Senior Research Associate in the Development Strategies and Governance Unit, based in Cairo. Her research interests include applied economic development, trade, and spatial economics, with a focus on topics relevant to social protection, food, nutrition, and agriculture in the Middle East and Africa. 

Where we work

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Where we work

IFPRI currently has more than 600 employees working in over 80 countries with a wide range of local, national, and international partners.

Using Big Data and Machine Learning to Predict Poverty and Malnutrition for Targeting, Mapping, Monitoring, and Early Warning

Co-organized by Cornell University and Food Security Portal of IFPRI

July 28, 2021

  • 8:00 – 9:30 am (America/New_York)
  • 2:00 – 3:30 pm (Europe/Amsterdam)
  • 5:30 – 7:00 pm (Asia/Kolkata)

Increasingly plentiful data and powerful predictive algorithms have heightened the promise of data science for humanitarian and development programming.  As agencies increasingly embrace and invest in machine learning methods for poverty and malnutrition targeting, mapping, monitoring, and early warning, it is essential to recognize that different objectives require distinct data and methods. In this webinar, we highlight the differences between poverty and malnutrition targeting and mapping, the differences between structural and stochastic deprivation, and the modeling and data challenges of early warning systems development based on machine learning methods. We also present two studies that apply machine learning methods to predict poverty and malnutrition.

This webinar is the second of a two-part webinar to present new data and findings from ongoing research under the United States Agency for International Development (USAID)-funded project “Harnessing Big Data and Machine Learning to Feed the Future”, based at Cornell University. Researchers and analysts from operational agencies are invited to join these events for a presentation and discussion of key principles, data sources, methods, and applications.