I am a philosopher of artificial intelligence investigating the human use and misuse of mathematical and computational tools in knowledge production and decision-making. I focus particularly on emerging applications of machine learning (ML) in scientific and social contexts, aiming to promote both epistemically and ethically sound practices. At present, I am a postdoctoral research associate jointly affiliated between the Center for Information Technology Policy (CITP) at Princeton University and the Natural and Artificial Minds Initiative (NAM) of the Princeton AI Lab. I am also the principal investigator on a grant from the Alfred P. Sloan Foundation’s Metascience and AI funding scheme assessing the epistemic credentials of AI in science evaluation. I earned my doctorate in philosophy in 2025 from the University of Cincinnati.

My doctoral research developed a view of mathematical representation in which applied mathematical and computational models act as conceptual prosthetics: extensions of our cognitive capacities for manipulating abstract representations. This framework has been applied in three main directions: illuminating foundational questions in the philosophy of science, clarifying ML’s contributions to scientific knowledge, and constraining ML to epistemically justified roles to reduce social harms.

My current research continues this in several directions. Work in the direction of AI ethics examines the relationship between the epistemic reliability of ML systems and their propensity to cause harm, interrogates the assumptions of algorithmic fairness, and develops formal tools for evaluating discriminatory tendencies in AI systems. While continuing my study of the integration of AI/ML tools into basic science and its epistemological implications, I have also turned to investigate proposed uses of such tools in science evaluation as well.