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Eric studied engineering physics at the University of California, Berkeley, and began his research career with wonderful mentors at Lawrence Livermore National Laboratory. In 2004, he completed his Ph.D. in Princeton's Program in Applied Computational Mathematics, advised by Professors Phil Holmes and Jonathan Cohen. His research focused on the interface between dynamical systems and neuroscience. Following his doctoral studies, Eric undertook postdoctoral training with Professor John Rinzel at New York University’s Courant Institute of Mathematical Sciences, where he worked on mathematical models in cognitive neuroscience, specifically the dynamics of neural circuits. At the University of Washington, Eric directs a working group focused on the dynamics of neural networks and populations. His research explores the intricate mechanisms that govern neural dynamics and seeks to understand how these systems encode information and make decisions about sensory experiences. Recent projects include analyzing the time course of decision-making in neural networks and employing graph-theoretic tools to address neural connectomics challenges. Eric actively collaborates with fellow theorists and neurobiologists, drawing on extraordinary datasets that enhance the comprehension of brain dynamics across various scales.
Department of Applied Mathematics, University of Washington • Seattle, WA
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