Zachariah (Zach) Cohen

About

Zach Cohen is a graduate student in Neuroscience and a member of the Drugowitsch Lab at Harvard Medical School. His research broadly focuses on developing normative theories for neural computations subserving dynamic behaviors, such as navigation and planning. Before coming to graduate school, Cohen worked as a software engineer in New York City. He was first introduced to theoretical neuroscience while completing his undergraduate degree in computer science at Princeton University, where he undertook independent research aimed at understanding how the brain represents sensory information involved in context-dependent decisions.

Research Focus

Cohen’s current research focuses on theoretical neuroscience, dynamic behavior under uncertainty, and navigational planning. Every day, humans and other animals make numerous decisions about where to go and how to get there. This process involves planning, a process of mentally simulating candidate trajectories using learned internal maps of the environment. Cohen’s research is focused on developing formal, testable theories concerning both the format of the cognitive representations agents use for efficiently and effectively planning in complex environments, as well as the structure of the neural activity that underpins these representations. To tackle these aims, Cohen leverages a mixture of tools from information theory, reinforcement learning, and geometric machine learning.