I aim to understand the computational and neurocognitive processes that underlie the
development of active learning and complex decision-making. I am especially interested in how these processes operate in social contexts. For instance, how do children and adolescents learn to predict the goals and preferences of their peers and then adjust their own decisions accordingly?
My research interests further extend to how these processes of learning and decision-making are affected by
psychopathology and adversity. This includes ADHD, Autism, social exclusion, and scarcity. In my research, I use neuroimaging ( fMRI) and computational modelling of behavior. For example, probabilistic inference (Bayesian) models where the decision-maker builds a belief over the state of the world and combines that with utility functions. This approach allows for quantification of latent variables that are not directly observable from behavior, such as beliefs and uncertainty. Open science is important for the quality and efficiency of research. My data and code are freely available on Github, OSF, or upon request. Visit the publications page to access these resources.
I am currently a postdoc funded by a NWO Rubicon award at New York University in the Computation and Cognition lab led by Todd Gureckis. I am collaborating with Cate Hartley (NYU), Anna van Duijvenvoorde (Leiden University), Gabriela Rosenblau (GWU), and Wei Ji Ma (NYU). I previously worked as a postdoc with Alan Sanfey at the Donders Institute and completed my PhD at the Radboud University mentored by Anouk Scheres and Toon Cillessen.