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. Head of CRiSS-LAB.
Cristian Candia studies how societies transform information into collective relevance through attention, memory, preferences, and coordination. His work combines computational social science, network science, AI, and large-scale behavioral data to understand how groups, institutions, and societies decide what matters.