Exploring complex social systems with a quantitative approach involves abstracting rich and nuanced data. Many tools for analyzing these data are then developed with assumptions that do not always reflect or incorporate more qualitative, or theoretical, observations of the systems in question.
SFI Complexity Postdoctoral Fellow Izabel Aguiar contends that what is lost in the process of strict quantification — a qualitative understanding of both nuance and pattern — creates potential blind spots in scientific fields that aim to quantitatively study human interactions. Her work aims to address this by motivating the development of mathematical and statistical methods informed by theories and observations from sociology, cognitive science, and anthropology.
Aguiar earned a B.S. from the Colorado School of Mines and an M.S. from the University of Colorado Boulder before receiving her Ph.D. in computational and mathematical engineering from Stanford University.
“My work focuses on the complicated ways that people can be connected to one another,” Aguiar says. “Finding ways those complicated relationships can be represented with networks, exploring how people’s perceptions of those networks differ, developing quantitative tools for understanding them that incorporate the work of qualitative scholars.”
Developing models that synthesize a rigorous balance of quantitative and qualitative fields in the study of complex social systems will be the focus of Aguiar’s work at SFI. She is curious about developing tools to study peoples’ perceptions about their social worlds, incorporating insights from cognitive science and sociology to help us learn more about our realities. Aguiar begins her fellowship in October.