My research focuses on the structure and origin of knowledge, guided by perspectives and methods from cognitive science, cognitive development, and computational modeling. By combining these, I hope to better understand the form and development of the basic commonsense reasoning that guides our interaction with the world and the people in it.
I'm interested in understanding why these humans don't pet me 24/7.
By studying the development of the human cognitive abilities that enable us to pretend that bananas are telephones, I seek to gain purchase on a set of theoretical questions concerning the relation between action, causal reasoning, and conceptual development.
How do humans intuitively understand what other people want? How do we navigate the tension between our own and others' needs in social interactions? I use developmental experiments and computational models to characterize how humans grasp and respond to others' goals, and how one’s own utility can affect interpretation of others’ goals, at times leading to successful cooperation and at other times leading to misunderstandings, searching for loopholes, and rule-bending.
I'm interested in using experimentation, modeling, and theory to explore the relationship between intuition and formal reasoning in cognition, and how people learn concepts in abstract domains such as science, programming, and mathematics.
I use the spaces of theoretical computer science, programming languages, and evolutionary theory to advance our understanding of the generative processes behind human intelligence.
I am interested in using methods from cognitive science, neuroscience, and computational modeling to understand the mechanisms behind common-sense reasoning, the underlying representations of abstract concepts, and the operations that build our compositional thoughts.
I'm interested in utilizing the methods from mathematics, statistics, and computational modeling to investigate the topics in causal reasoning and intuitive physics.