Photo of Carl Nordlund

Carl Nordlund

Assistant Professor, Docent

My substantive research interests include inter-ethnic relations, political ecology, and economic and human geography, as well as developing network-analytical methods, specifically blockmodeling techniques and methods for valued networks.

Welcome to my LiU profile page!

I am an assistant professor at the Institute for Analytical Sociology (IAS) and director of our MSc program in Computational Social Science. 

I obtained my PhD in human ecology from the Department of Human Geography at Lund University in 2010, with previous studies in computer science and engineering, mathematics, economic history, development studies and languages. I subsequently had several postdoctoral fellowships at Central European University, Budapest, with joint positions at the Department of Political Science and Center for Network Science, with short stints at European University Institute, Florence, and Department of Economic History, Lund university. My work has mainly been published in Social Networks, as well as Network Science, Geographical Analysis, Journal of European Integration, and Studies in Comparative International Development.

At IAS, my main research area is ethnic integration, specifically studying patterns of inter-ethnic family formation using population register data. Since 2021, I lead a large Nordic research group on the network dynamics of ethnic integration. Funded by a 4-year NordForsk interdisciplinary grant, a total of 12 researchers and PhD students in Sweden, Denmark and Finland will study ethnic relations and integration in three social domains: family formation, residential segregation, and labor market discrimination. In addition to this, I continue developing network-analytical methods, particulary deterministic blockmodeling techniques and methods for valued/weighted networks. I am also the director for our international 2-year MSc program in computational social science, and I teach introductory courses in statistics, programming and data science.

In addition to conventional scholarly output, I also do a bit of software development. Although I teach R in our courses, my preferred language of choice is C#, in which I have developed multiple Windows clients for the analysis and visualization of networks, as well as C#/Unity applications for bivariate visualizations of demographic data. I am also well-versed in Python, PHP, .js, and SQL, used in multiple web projects I am running (see personal homepage).

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2020

2019

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