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Konstantin Zuev is a Teaching Professor in the Division of Engineering and Applied Science at the California Institute of Technology, focusing on a wide range of courses in applied mathematics, including linear algebra, applied probability, stochastic processes, complex analysis, differential equations, statistical inference, and statistical learning. His research interests lie primarily in network science, where he investigates network data analysis, models of complex networks, network resilience, and dynamic processes within these networks. Notably, he has a particular interest in course-prerequisite networks that model interactions between courses and represent the flow of knowledge within academic curricula. Professor Zuev also serves as the undergraduate option representative for the Information Data Science option, contributing to the development of curriculum in this emerging area of study.
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