**Speaker**: Alex John Quijano

**Title**: Introduction to Dynamic Mode Decomposition and Applications

**Abstract**: Dynamic Mode Decomposition (DMD) is a data-driven approach to mathematical modeling. Systems such as turbulent fluids, biological systems, finance, and climate can be characterized as high-dimensional and nonlinear dynamical systems. Given a high-dimensional dynamical system in a form of time-series data, DMD computes a matrix via Singular Value Decomposition (SVD) that represents the dynamics of the system. Not only it can reconstruct the time-series, but it can also produce short term predictions. This talk introduces the DMD technique and how it can be used to discover the dynamics of a system given some data.