DanielAguirre Salamanca

Daniel is a Senior Associate in the Data Analytics Unit at the World Justice Project. His work focuses on developing methodologies and technical infrastructure to measure rule of law across countries, including data collection strategies and the integration of AI-supported analysis of legal texts and media reporting. Daniel contributes to the development of early warning systems that analyze media coverage and public information to detect emerging attacks on judicial independence and coordinated narratives that may undermine public trust in courts. He also supports the data analysis and validation of WJP's global indicators, applying machine learning and statistical methods to expand the evidence base that informs reform efforts and policy dialogue worldwide. 

Before joining WJP, Daniel worked as a Senior Researcher and Data Scientist at Quantil, where he led the design and deployment of machine learning solutions for clients in the energy, insurance, and public sectors. His projects included multivariate time series segmentation, retrieval-augmented matching systems for workforce development, and distributed computing frameworks for large-scale economic scenario analysis. He also served as a Research Assistant at Universidad de los Andes, contributing to studies on digital drug markets, generative models for medical imaging, and transportation systems for urban planning. 

Daniel holds a Master's degree in Computer Science and a Bachelor's degree in Economics from Universidad de los Andes in Bogotá, Colombia, as well as a Bachelor's degree in Mathematics from Indiana University. He also serves as an Adjunct Professor at Universidad de los Andes, teaching courses in Data Science and AI at the Faculty of Economics and the Department of Computer Science.