Research Interests
- Developing general theories of cognition, focusing on cognitive processes.
- Understanding how mental representations allow us to interact flexibly with the world.
- Understanding the relevance of cognitive constructs for everyday behavior.
To accomplish this, I combine experimental and individual differences approaches and use computational & statistical models.
Selected Publications
- Thalmann, M. & Schulz, E. (2026). Modeling, Measuring, and Mapping Individual Differences in Mental Object Representations. PsyArXiv.
- Voudouris, K., Thalmann, M., Kipnis, A., Hernández-Orallo, J., & Schulz, E. (2026). Measuring What AI Systems Might Do: Towards A Measurement Science in AI. arXiv.
- Thalmann, M., Witte K., & Schulz, E. (2025). Model-based exploration is measurable across tasks but not linked to personality and psychiatric assessments. Scientific Reports, 15(1), 1-19.
- Thalmann, M. & Schulz E. (2025). How Can We Characterize Human Generalization and Distinguish It from Generalization in Machines? Current Directions in Psychological Science, Online First, 1–8.
- Haridi, S., Schulz, E., & Thalmann, M. (2025). Context Size and Set Size Effects: The Relevance of Specific Cues When Searching Long-Term Memory. Computational Brain & Behavior.
- Binz, M. et al. (2025). A foundation model to predict and capture human cognition. Nature, 1–8.
- Thalmann, M., Souza, A. S., & Oberauer, K. (2019). How does chunking help working memory? Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(1), 37–55.
