Natalia Vélez

Natalia Vélez serves as an Assistant Professor at Princeton University, where her research bridges cognitive science and social dynamics to investigate the foundations of human collaboration. Her work examines how individuals and communities combine limited knowledge and resources to achieve collective outcomes greater than individual capabilities.

Her educational foundation includes:

• Ph.D. from Stanford University

Dr. Vélez's research program focuses on the cognitive architecture and social ecology of collaboration. At the micro-level, her lab studies how individuals learn about collaborators, share knowledge, and distribute labor through behavioral experiments with children and adults. At the macro-level, she investigates community-wide dynamics using large-scale dataset analyses. Her methodological toolkit integrates Bayesian cognitive modeling, functional neuroimaging (fMRI), and computational simulations to build unified theories of collaborative behavior.

Analysis of her 15 most recent publications (2023-2024) reveals three dominant research trajectories: 1) Computational models of social cognition in collaborative contexts, 2) Empirical investigations of effort valuation and responsibility attribution in teams, and 3) Interdisciplinary applications of AI to understand human cooperation. Her work consistently bridges theoretical cognitive science with real-world collaborative challenges, emphasizing the interplay between individual mental processes and group-level phenomena.

Dr. Vélez currently advises graduate students Bella Fascendini, Ham Huang, and Chantal Valdivia. Her research program demonstrates sustained funding through methodologically sophisticated projects spanning cognitive neuroscience, behavioral economics, and artificial intelligence, though specific grant details aren't provided in source materials.

She directs the Princeton CoLab, an interdisciplinary research hub that combines experimental psychology, computational modeling, and neuroimaging to study collaboration. The lab fosters methodological innovation through projects examining virtual community dynamics, embodied AI agents, and neural correlates of social learning, positioning itself at the intersection of human cognition and collective intelligence research.