Memory, science, and correction
The 2026 FONDECYT Regular grant on collective memory decay in science consolidates a distinctive research line: why some knowledge remains active even after being invalidated.
View FONDECYT projectHow societies decide what matters?
CRiSS-LAB studies how people, groups, and institutions decide what deserves attention, what is remembered, what is preferred, and how decisions become coordinated in environments saturated with data, AI, and information.
We combine social theory, network science, dynamic models, causal inference, AI, and experimental platforms to understand these processes and design better decision systems for institutions, organizations, and public life.
Welcome to CRiSS-LAB
CRiSS-LAB is the Computational Research in Social Science Lab at Universidad del Desarrollo in Santiago, Chile, directed by Cristian Candia, Ph.D. We study how people, groups, institutions, and societies decide what matters in environments saturated with data, AI, and information.
Our work examines how attention, memory, preferences, and coordination shape collective relevance: what becomes visible, what is remembered, what is preferred, and how decisions become coordinated action. We combine computational social science, network science, dynamic models, causal inference, AI, and experimental platforms to generate evidence for education, science, culture, organizations, public policy, and digital environments.
Cristian Candia, Ph.D.
Head of CRiSS-LAB.
What we study
How do people, groups, and institutions decide what matters?
CRiSS-LAB studies how, in environments saturated with data, AI, and information, societies produce collective relevance: what receives attention, what is remembered, what is preferred, and how decisions become coordinated. We combine computational social science, network science, dynamic models, and experimental platforms to understand these processes and design better decision systems.
Models for social systems
We combine network science, statistical physics, causal inference, machine learning, and text analysis to move from individual traces to aggregate explanations.
View researchInstitutional impact
The lab's applied platforms bring this research into education, school coexistence, public deliberation, culture, mobility, organizations, and risk analytics.
View projectsPeople Behind CRiSS-LAB
Researchers, students, and Data & AI professionals building computational social science from Chile.
Our team connects theory, data, and applied technology to study collective memory, learning, cooperation, and decision-making in real social systems.
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