MS&E 321 Stochastic Systems (Spring 2017)

Department of Management Science and Engineering,
Stanford University


    Location: Thornton 110
    Time: Tuesday 4:30 PM - 7:20 PM

    Instructor: Prof. Jose H. Blanchet
    Email: jblanche "at" stanford "dot" edu

Course Description

    This course addresses fundamental topics in the modern theory of stochastic processes, with emphasis on a broad spectrum of applications in engineering, economics, finance, and the sciences. The course carefully treats Markov chains in discrete and continuous time, Perron-Frobenius theory, Markov processes in general state space (including Harris chains), Lyapunov functions and supermartingale arguments for establishing stability, theory of regenerative processes and related coupling ideas, rare event analysis via large deviations, renewal theory, martingales, Brownian motion, and associated diffusion approximations. At the conclusion of this course, students will have a working knowledge of the mathematical tools and models that represent the cutting edge in the theory and application of stochastic processes to complex systems. The ideas will be illustrated by appealing to examples chosen from queueing theory, inventory theory, and finance.


    All course materials will be distributed via Canvas.