Our lab investigates how cognitive processes such as memory, learning, and decision-making develop and operate, with a focus on the domains of language and concepts. We leverage machine learning methods and cognitive models in order to understand how people actively adapt their behavior to navigate a changing environment.

Our Research

Our research explores the mechanisms of cognition through the lens of computational models and statistical methods. One current focus of the lab is to use Bayesian psychometric models as a means to build testable, extensible theories of early language development, combining large datasets on children’s early learning environment (e.g., video and audio from head-mounted cameras), tested on databases of early productive vocabulary.

Our Projects

The “standard” model of early language development captures the field’s consensus view that words are learned through a process of accumulation from speech that is either directed at the child or overheard in their environment. This Bayesian psychometric model can be fitted to individual children, and also makes predictions about learning trajectories of individual words. We have extended this approach in a cognitive model that takes into account individual variability in processing speed.

Our Team

We love to collaborate on interesting projects, and are currently accepting bachelor and masters students - feel free to reach out if you’re interested!