My research focuses on developing flexible statistical and machine learning methods to accurately identify latent (unobserved) structures in social, behavioural and health data. I use these methods to study learning acquisition, health inequalities, public opinion, humanitarian decision-making, fairness in educational testing and interpretability in psychological measurement. I often collaborate with domain experts from various fields, including economics, psychology, political science, the educational testing industry and NGOs.
I am currently building a research lab around the project Next-generation latent variable models for social data science, funded by the Swedish Research Council. Interested in joining the lab as a PhD student or postdoc, visiting us, or collaborating? Please get in touch.
Brief CV:
2023-2026: Assistant Professor in Statistics, School of Mathematical Sciences, Lancaster University
2021-2023: Postdoc, Department of Statistics, London School of Economics and Political Science
2020-2021: Postdoc at INRIA, team MAASAI (Models and Algorithms for Artificial Intelligence) and Laboratoire J.A. Dieudonné at Université Côte d'Azur
2020: PhD in Statistics, Umeå University
See my personal website for more information: https://gabrieltwallin.github.io/