Network Science and Complex Systems
This course introduces network science as a technical and conceptual language for studying social, technological, biological, and organizational systems. Students work with graph construction, centrality, communities, null models, diffusion, link prediction, and graph-based machine learning.
The public course site is available at networks.criss-lab.com.
Cristian Candia
Associate Professor, Data Science Institute, School of Engineering, Universidad del Desarrollo, Chile. Director of CRiSS-LAB.
Cristian Candia is a computational social scientist studying human and collective behavior with large-scale data, network science, experiments, and AI.