People excel at real-life tasks that remain challenging for modern AI — creatively solving problems they have not seen before, generalizing from a few examples, and inventing new tools. What is it that makes us so efficient?

I am a computational cognitive scientist studying intelligent reasoning in humans and machines. My work focuses on how intelligent agents structure and represent knowledge, plan, and learn from limited data. I combine probabilistic modelling, neurosymbolic methods, and behavioural experiments to develop formal accounts of cognition, and use them to inform the design of AI systems that reason like minds do. Publications are available on Google Scholar.

Research interests

computational cognitive science, probabilistic reasoning, structured representations and inductive biases, theory of mind