ISE 589: Computational Applications of Sustainability and Resilience
Computational approaches to measuring sustainability, risk, and resilience using decision analysis, data science, stochastic processes, optimization, and simulation.
Instructor: Ben Rachunok
Term: Fall
Course overview
ISE 589 introduces sustainability, risk, and resilience as quantitative systems concepts. The course begins with foundational frameworks—including IPAT, the Kaya identity, and risk as scenarios, uncertainty, and consequences—then examines how computation can support measurement and decision-making.
Topics
- Sustainability, risk, and resilience theory
- Decision-making under uncertainty
- Data science and statistical analysis
- Stochastic processes and simulation
- Optimization for sustainability and resilience
- Climate change and sea-level rise
- Natural-hazard impacts and infrastructure disruption
- Distributional impacts, the climate gap, and climate retreat
- Eco-economic decoupling
Format and preparation
Assignments and the final project are programming-based. Students develop a computational project in an application area of their choosing. The course is designed for master’s and Ph.D. students in Industrial and Systems Engineering, Operations Research, Civil Engineering, and related fields; qualified undergraduates may enroll with instructor permission.
Students should be comfortable with an object-oriented programming language and have prior exposure to applied statistics and optimization. Current students should use NC State WolfWare for official materials and deadlines.