Research
Research themes and questions of CogDyn Lab
Our lab studies cognition as a dynamic system: how mental representations, decisions, and behavior change across time, task, and environment.
Main questions
- How do people learn and update beliefs from noisy evidence?
- How do attention, memory, and decision processes interact over time?
- How can computational models explain individual differences in behavior?
- How do people understand, trust, and collaborate with AI systems?
Research areas
Learning and adaptation
We model how people adapt to changing environments, learn from feedback, and transfer knowledge across contexts.
Decision-making and cognitive control
We investigate how people allocate attention, control actions, resolve conflict, and make decisions under uncertainty.
Computational modeling
We use mathematical, statistical, and machine-learning models to formalize hypotheses about cognition and behavior.
Human-AI interaction
We study how humans interpret, rely on, and adapt to intelligent systems.
Methods
- Behavioral experiments
- Computational modeling
- Bayesian/statistical inference
- Machine learning and simulation
- Online experiments and longitudinal data
- Open science and reproducible workflows