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We study the computational mechanisms by which humans efficiently encode and retrieve memories. The ultimate aim of this research is to leverage these theoretical insights to enhance memory performance in humans and design more effective artificial learning agents.

To develop a theory that generalizes, we build computational models to unify empirical findings across different tasks and to bridge memory research conducted in well-controlled laboratory environments and naturalistic settings. 

We are grateful for the funding support from the National Science Foundation and Rutgers Brain Health Institute.