My work addresses how learning agents in partially observed environments acquire and preserve epistemic behavior — the structured, information-seeking patterns that make agents effective under uncertainty. I am interested in both the theoretical foundations of this behavior and its practical implications for the deployment and auditing of trained policies.

I am particularly interested in healthcare and clinical decision support as application domains, where epistemic failure carries real cost and the need for auditable behavior is high.