• ESI 4313: Operations Research 2

This is an undergraduate core course that introduces stochastic models and methodologies for performance analysis and optimization of stochastic systems. Topics include the method of conditioning, discrete-time Markov chains, Poisson process, continuous-time Markov chains, and renewal theory.

  • ESI 6346: Decision Making Under Uncertainty

This is a course offered to working professionals pursuing an engineering management master’s degree. The course introduces quantitative models for decision-making in environment where uncertainty is present. Topics include fundamentals of probability, utility theory, decision trees, Markov chain modeling, and fundamentals of stochastic optimization.

  • ESI 6546: Stochastic Modeling and Analysis

This is a PhD core course that primarily focuses on stochastic processes, with emphasis on probabilistic reasoning and model building. Specific topics include a review of probability theory, the method of conditioning, discrete- and continuous-time Markov chains, renewal theory, and Brownian motions. Applications in queueing, reliability, inventory, logistics, and finance are also discussed.