I'm currently working on revising this page :) 

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When I describe myself as a philosopher of "the cognitive sciences" I have in mind the areas of cognitive science found at the intersection of philosophy, computer science, artificial intelligence, and neuroscience. 

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I wrote my dissertation on theories of computation. In my dissertation I develop a framework that articulates three distinct questions at stake in the debate: implementation, interpretation, and individuation. I argue that theories that address the nature of physical computation fall into one of three categories, each answering one of the questions I define. The framework proposes that non-semantic theories are best understood as answering the implementation question (what is the relation between a formal computational structure and a physical system), semantic theories are best understood as answering the interpretation question (which computational process does the physical system perform), and mechanistic accounts answer the individuation question (how do we distinguish computing systems from non-computing systems). Once these questions are clearly defined, we can see how the different theories provide compatible answers in that they each address a different aspect of physical computation. Part of this project is revisionary in that I propose we understand various theorists as answering a different question than the one they take themselves to be answering. However, although my project is revisionary, I take it to be friendly toward the views that have been offered in that my framework makes room for different accounts within a unified picture, rather than settling on one way to address the nature of physical computation. 

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The framework that I develop in my dissertation heavily influences my current research program. The three questions I define can be imported into the cognitive sciences which rely heavily on computationally modeling neural processes. We can understand computational models as doing two things (although not all computational models do both things at once): they provide a hypothesis for how the brain performs computations and also what the brain computes (typically defined in terms of a mathematical function). This makes the implementation and interpretation questions directly relevant to computational modeling practices. Much of my work centers around these questions, leading to research that touches on several relevant areas in philosophy of science such as the realism debate in philosophy of science, the nature of physical computation, the nature of explanation, and sometimes, the debate about cognitive ontology. ​​​