Chilam – Laboratory for the Simulation of Complex Adaptive Systems

Chilam is a recent initiative, led by the C3 – Centro de Ciencias de la Complejidad of the Universidad Nacional Autónoma de Mexico, that unites several existing research projects that share both a common purpose – to apply a big-data and a machine learning-based approach to problems of high social impact – as well as a common theoretical framework – Bayesian machine-learning prediction models.

The first and most developed project is the SPECIES Platform, developed in collaboration with the Consejo Nacional de la Biodiversidad (CONABIO) since 2013 and based on a novel, innovative approach to spatial modelling and aimed towards modelling biodiversity patterns and the ecological aspects of emerging diseases.

Project 42, developed since 2014, on the other hand, is directed at providing a unique, highly multifactorial data set for the study of obesity and metabolic diseases and a Bayesian modelling platform for the Chilam projects involve over 80 researchers and students from multiple disciplines across the exact, life and social sciences.