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Operations

Associate Professor of Operations

Portrait of Anton Braverman, Faculty at the Kellogg School of Management

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, as well as healthcare operations.

  • PhD, 2017, Operations Research, Cornell University
    MS, 2015, Operations Research, Cornell University
    BS, 2012, Math and Statistics, University of Toronto
  • Assistant Professor, Operations, Kellogg School of Management, Northwestern University, 2017-present
  • 2017 Best Publication Award, The Applied Probability Society of INFORMS, 2016-2017

Queueing Networks: Models, Algorithms and Emerging Applications (OPNS-522-0)

This course aims to expose students to advanced methods in stochastic analysis and develop a toolbox of probabilistic analytical techniques. To focus the discussion, the course will be centered around queueing networks, which serve as building blocks in many modeling applications. Topics covered include fundamental queueing models, fluid and diffusion processes, limit theorems and approximations, and stochastic control. To discuss the algorithmic/computational elements of stochastic control, we will touch on approximate dynamic programming and explore how it is used in the control of queueing networks.

Stochastic Processes I (OPNS-516-1)

The course prepares the student with an understanding of Stochastic Processes. This course covers the following topics: Poisson Processes, discrete-time Markov chains, and continuous time Markov chains. It applies these concepts to queuing systems. Students are expected to have some background in probability.