Konstantin Zuev is a Teaching Professor of Computing and Mathematical Sciences. He teaches a broad range of courses in applied mathematics and statistics on subjects such as linear algebra, applied probability, stochastic processes, complex analysis, differential equations, statistical inference, and statistical learning. His research focuses on network science, network data analysis, models of complex networks, network resilience, and dynamic processes on complex networks. Particular interests include course-prerequisite networks that model interactions between courses and represent the flow of knowledge in academic curricula. Professor Zuev also serves as the option representative for the Information and Data Science option.