I am currently an associate professor in Statistics at the Department of Statistics, Uppsala University and affiliated with the Institute for Analytical Sociology at Linköping University. I am also a member of ELLIS and the Young Academy of Sweden.
My research interests lie at the intersection of Bayesian statistics, probabilistic machine learning, and social science applications of text analysis. I focus particularly on methods for probabilistic programming, model evaluation and diagnostics, as well as statistical methods for large-scale text data, such as legal and parliamentary corpora. A recurring theme in my work is how statistical models can be made more robust, interpretable, and useful for research on societal issues.
Find more information about me and my research at https://mansmagnusson.com/ and Google Scholar.
Sivula, T., Magnusson, M., Matamoros, A. A. & Vehtari, A. (2025). Uncertainty in Bayesian leave-one-out cross-validation based model comparison. Bayesian Analysis.
Hurtado Bodell, M., Magnusson, M. & Mützel, S. (2022). From Documents to Data: A Framework for Total Corpus Quality. Socius.
Östling, A. et al. (2023). The Cambridge Law Corpus: A Corpus for Legal AI Research. NeurIPS.
Magnusson, M., Andersen, M. R., Jonasson, J. & Vehtari, A. (2020). Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data. AISTATS.
Hurtado Bodell, M., Magnusson, M. & Keuschnigg, M. (2024). Seeded Topic Models in Digital Archives: Analyzing Interpretations of Immigration in Swedish Newspapers, 1945–2019. Sociological Methods & Research.
