Laura Fürsich

I am a Post Doctoral Fellow at the Mansueto Institute for Urban Innovation at the University of Chicago and the Institute for Analytical Sociology at Linköping University.
My research examines how social inequalities persist and evolve within spatial and institutional contexts. I focus in particular on the dynamic relationship between social networks, residential segregation, and stratification.


As a computational social scientist, I integrate approaches from sociology, urban studies, and complexity science, combining agent-based modeling,
information theory, discrete choice models, and network analysis with large-scale administrative data from Sweden and the Netherlands. I am particularly interested in how statistical information can be used to uncover the mechanisms behind spatial inequality, social influence, and intergroup relations. This perspective allows me to move beyond description, identifying patterns and relationships in data that shed light on both enduring and emerging forms of inequality.

At the Mansueto Institute, I explore how cities function as structured spaces of interaction, revealing feedback loops between place, opportunity, and social mobility. My broader aim is to develop computational and data-driven approaches that not only advance theory but also inform equitable urban policy.

I hold a PhD in Analytical Sociology from the Institute of Analytical Sociology at Linköping University, Sweden. Before my doctoral studies, I earned a Bachelor’s and Master’s degree in Social Economics from the Friedrich Alexander University of Erlangen-Nürnberg.

Projects

Dissertation


How do social contexts shape interaction opportunities, influence networks, and drive segregation patterns?

Social Networks and Residential Segregation


I model segregation by examining how social contexts shape interaction opportunities, influence networks, and drive segregation patterns.

Mapping the Complete Network of the Swedish Population

We map a full-population multiplex network to understand
integration and stratification across domains

Complex Systems Approach to Life Course Research

I use advances in information theory and statistical modeling to untangle how location, demographics, and education shape income trajectories over the life course.

Residential Consolidation


How does the correlation of attributes shape residential segregation and collective efficacy?

Urban Growth


How do patterns of residential sorting and neighborhood selection cumulatively shape long-run urban inequality and growth?

Teaching

I am teaching in the Master’s programm in Computational Social Science at LiU in the following courses:

  • Agent-Based Modeling
  • Segregation and Inequality
  • Behavioral Mechanisms in the Social Sciences

Other Materials

I replicated Reardon et al. 2008 using the SEG package in R. You can find the repository here.

Projects at Graduate Workshop in Computational Social Science at Santa Fe Insitute in 2022: Here’s a list of all the projects we worked on during our time in Santa Fe.