Miguel Camacho Horvitz is a Predoctoral Researcher in the Economics team at EIT, committed to understanding and addressing diverse forms of inequality. His research combines empirical methods - particularly machine learning and text analysis - to examine global disparities in health, education, and labour market outcomes, leveraging administrative, survey, and unstructured text data.
In recent years, Miguel has worked at the intersection of economics and AI with leading institutions including the World Inequality Lab, J-PAL, NBER, OECD, and the Norwegian School of Economics.
He holds two Master鈥檚 degrees: one in Computer Science from Stanford University and another in Economics from the Paris School of Economics, and brings several years of experience as a machine learning engineer in Silicon Valley.
At EIT, Miguel seeks to bridge academic research and private-sector innovation to advance equitable socioeconomic outcomes across health, climate, and technological development.
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