Stein’s Method for Diffusion Approximations in Queueing Theory: A Tutorial

Title: Stein’s Method for Diffusion Approximations in Queueing Theory: A Tutorial

Speaker: Prof. Anton Braverman, Professor, Northwestern University

Time: 7:00 PM - 8:00 PM (IST)

Date: 4 November 2025

Venue: Online on Zoom

Abstract: The generator comparison approach of Stein’s method is a framework used to compare the stationary distributions of any two Markov processes and derive bounds on their distance under some integral probability metric. Notably, the approach does not require coupling the two distributions.
Over the past ten years, this capability has been exploited in queueing theory to better understand diffusion approximations. In this talk, I will give a tutorial on the use of this approach and the subsequent results that have been achieved with its help.

Bio: Anton Braverman joined the Operations group at Kellogg in 2017. He completed his PhD in Operations Research from Cornell University, and holds a Bachelor's degree in Mathematics and Statistics from the University of Toronto. Anton's research is focused on stochastic modelling and applied probability. Some application domains of interest include ridesharing services and revenue management.

ALL ARE WELCOME.