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Konstantin Zuev is a Teaching Professor in the Computing Mathematical Sciences at the California Institute of Technology. He teaches a broad range of courses in applied mathematics and statistical subjects, including linear algebra, applied probability, stochastic processes, complex analysis, differential equations, statistical inference, and statistical learning. Professor Zuev's research primarily focuses on network science, specifically on data analysis, network models, and dynamics of complex networks. His interests extend to network resilience and dynamical processes, with a particular emphasis on course-prerequisite networks that illustrate interactions between courses and represent the flow of knowledge through academic curricula. Additionally, he serves as the undergraduate option representative for the Information Data Science option.
Most Caltech graduate programs are PhD-only. GRE General and Subject tests vary by department; many have made them optional or no longer accept them.