Semester: Fall 2023
Target Audience: Graduate students in relevant disciplines
Delivery Method: in-person
This course is offered by Prof. Saurabh Amin and I had the opportunity to be a guest lecturer on 'large-scale energy infrastructure planning under uncertainty' where I covered Benders decomposition, sample average approximation, and robust optimization. I was also mentoring some of the class projects related to energy systems.
Semester: Spring 2021
Target Audience: Junior/senior undergraduate students in ISE and similar disciplines
Delivery Method: hybrid (in-person/virtual)
I taught this class in my 4th year of PhD as part of the teaching certificate offered by NCSU. The delivery method was hybrid and the course offered an introduction to mathematical modeling, analysis, and solution procedures applicable to stochastic processes.
Python for ISE-362 [slides]
Review of Probability [slides]
Reliability Basics [slides]
Discrete-time Markov chain (DTMC) [slides, example code and data]
Markov decision process (MDP) [slides]
Continuous-time Markov chain (CTMC) [slides]
Queueing theory [slides]
Renewal theory [slides]
