MATEO DULCE RUBIO
Mathematician and Economist from the Universidad de los Andes, and Master in Economics from the same university, degree in which he obtained the Cum Laude degree. He serves as Director of the Data Mining area in Quantil | Applied Mathematics, where it is dedicated to the design, development and implementation of mathematical models and machine learning for the resolution of practical problems of industry, government, and academia. He has extensive experience in text mining and natural language processing working on the development of algorithms for the extraction of text information, sentiment analysis, construction of conversation topics, and machine learning in legal documents, contracts, social networks, among others. He has been the leading developer in the implementation of mathematics models applied to public safety for the prediction of hot spots, location of new police equipment, and prioritization of video surveillance systems. Additionally, it has implemented statistical analysis models for the prediction of bank client disaffiliation, spatial analysis and the occurrence and progression of high-cost diseases in Colombia, public transport data analysis for operator performance metrics, among others.