CEA

Project approved in Call FAEPEX/PRP 14/2025, More Women in Research. This project tackles the critical global challenge of food and nutritional insecurity, particularly within Latin America’s structurally unequal landscape. It proposes a multidisciplinary approach leveraging frontier Machine Learning (ML) techniques, specifically explainable AI (xAI) and interpretable ML (iML), to generate robust empirical evidence. The research centers on Brazil’s Bolsa Família Program as a case study, aiming to provide nuanced insights into its implications and limitations in combating hunger. This data-driven strategy directly addresses the need for interpretable evidence to support public policy formulation, with expected applicability to similar contexts in Mexico and across Latin America. This initiative, by fostering advanced interdisciplinary research and strengthening collaborative ties between institutions, further contributes to the internationalization of scientific knowledge and enhances the presence of women in key scientific and technological fields.

Pesquisadores CEA

Ivette Raymunda Luna Huamani

Professora associada

E-mail

iluna@unicamp.br

Artigos