Dominik Deffner

Dominik Deffner serves as a Qualifikationsprofessur (W1, Tenure Track W2) for Computational Modeling of Behavior at the Department of Psychology, Philipps University of Marburg. His research group, Computational Modeling of Behavior (AG Deffner), is housed in the Institute Building at Gutenbergstraße 18 in Marburg. Deffner's work bridges cognitive science, evolutionary anthropology, and social psychology through interdisciplinary approaches combining dynamic group experiments, cultural evolution studies, and computational modeling.

Deffner's educational background includes a PhD (Dr.rer.nat.) from the Max-Planck-Institute for Evolutionary Anthropology in Leipzig (2018-2021), an MSc in Evolutionary and Comparative Psychology from the University of St Andrews, UK (2016-2017), and dual undergraduate degrees in Psychology and Comparative Cultural and Religious Studies, Philosophy from Philipps-University Marburg (2012-2016). Prior to his current position, he worked as a postdoc at the Max-Planck-Institute for Human Development and Science of Intelligence Cluster in Berlin (2021-2024).

His research interests focus on understanding how individuals and collectives adapt to changing and uncertain environments through cognitive processes and social/cultural dynamics. Deffner's work primarily investigates collective dynamics and cultural evolution, cognitive modeling and Bayesian statistics, causal inference, cross-cultural comparative methods, and collective foraging. He combines immersive computer games, field research, and statistical modeling to study social cognition in naturalistic groups, particularly examining how visual-spatial dynamics drive adaptive social learning in complex environments.

Analysis of Deffner's recent publications reveals a strong emphasis on interdisciplinary research that bridges theoretical frameworks with empirical data. His work spans computational approaches to cultural evolution, collective decision-making processes, risk-sensitive learning strategies, and causal inference methodologies. A notable trend is his integration of Bayesian statistics with agent-based modeling to understand social learning dynamics across different contexts, from human groups to animal behavior studies. His research increasingly focuses on developing statistical workflows that enable robust causal inferences in cross-cultural research.

As an academic advisor, Deffner offers thesis opportunities in both empirical work (interactive group experiments, data analysis) and statistical/theoretical modeling (cognitive modeling, collective behavior, cultural evolution). His research group welcomes students interested in social learning, decision research, cultural evolution, group processes, and advanced Bayesian data analysis methods. While specific grant information isn't detailed in the provided texts, his affiliation with the Max Planck Society and publication in high-impact journals suggest successful funding acquisition for his research program.

Deffner leads the Computational Modeling of Behavior research group, which investigates cognitive decision-making processes in groups interacting in natural and complex environments. The group combines immersive computer games and field research with statistical modeling to better understand collective dynamics in real-world contexts. Current research directions include social cognition in naturalistic groups, social learning and cultural evolution, causal inference and statistical workflows, and flexibility and adaptation in both human and non-human animals.