CSE 675LEC - Stochastic Simulation and Inference

An emerging application for the stochastic process is analyzing complex natural and social systems using data collected from sensor networks and the World Wide Web that tracks the temporal evolution of those systems. By applying the stochastic process to data, we can improve commuter traffic, tune organizational efficiency, and control the spread of epidemics. In this course, we will learn how to construct and simulate the Markov processes that are the common abstractions of many dynamic systems, and learn the mathematical properties of these processes. Overall, this hands-on course trains students to apply stochastic-process thinking to the temporal dynamics of complex systems, as captured by data.

Credits: 3

Term Typically Offered: Fall

Requisites: Pre-Requisite: CSE 574.