Mercedes has led complex-multifaceted evaluations and evidence synthesis initiatives of the World Bank’s efforts in malnutrition reduction and the facilitation of demographic transitions in various countries. She also led the IEG flagship Results and Performance Report 2023 contributing to evidence-based decision-making within the World Bank Group. Her work is characterized by innovative applications of cutting-edge supervised and unsupervised machine learning techniques for portfolio identification and AI-driven content analysis.

She contributed to several thematic evaluations across human development sectors (Early Childhood Development, Higher Education, Health Service Delivery), and coordinated a learning product on value-for-money analysis. She also leads and peer-reviews micro evaluations in the Health, Nutrition, and Population sector.

Prior to joining IEG in 2014, Mercedes worked at the Social Protection and Health Division of the Inter-American Development Bank, and think tanks such as the CERGAS of the Bocconi University in Italy and CEDES in Argentina. Her extensive research experience spans a broad spectrum of topics, encompassing performance-based financing, benefit incidence analysis, economic evaluations, and impact evaluation.

Mercedes holds a Ph.D. in Economics from the University of Rome Tor Vergata in Italy and a Doctoral Program in Applied Health Economics and Policy from SSPH+ in Switzerland.