PhD Student, Second Year
Kim is interested in research of numerical analysis methods for partial differential equations with random coefficients, dynamical systems, and probability theory. She wishes to pursue applications in systems that are subject to inputs, interactions, or environments that can only be known approximately or described statistically. Before beginning her PhD studies, Kim worked in quantitative investment analysis, where she gained experience modeling stochastic processes, and her bachelor’s thesis examined discrete chaotic dynamical systems in economic models. She is also interested in research at the intersection of computational neuroscience and machine learning, particularly deep neural networks. Outside of mathematics, Kim enjoys playing the piano, photography, and powerlifting.