Our group studies complex natural-human systems in order to: 1) improve understanding of new risks to people and the environment across sectors and scales; and 2) design new approaches for mitigating these vulnerabilities. We use engineering fundamentals, operations research and a wide range of analytical and statistical approaches to build high resolution, mechanistic models of real-world systems. Then we use high performance computing to simulate system dynamics under uncertainty and stress, with the ultimate goal of informing optimal system design and/or control strategies.
We have an especially strong interest in energy system decarbonization and exposure to weather and climate uncertainty and extremes. Much of our work is ultimately aimed at supporting real-world decision-making regarding management of/ investment in natural resources and critical infrastructure, and we frequently interact with and collaborate with actual stakeholders (e.g., electric power utilities). We aim to provide students with modeling and analytical skills and sector-specific knowledge– as well as a professional network spanning academia, government, and the private sector– that they can leverage to pursue a range of post-graduate employment opportunities.
Please feel free to navigate through the menu topics to learn more about different projects we have finished or are currently working on — or, you can get a sense for our research from the YouTube video below, a seminar Jordan gave at UNC Chapel Hill in 2020.
Interested in joining the group?
If you: are interested in working on relevant, cross-cutting projects that deal with the power grid, extreme weather and climate change, environmental sustainability, and financial/economic markets; and you can code; and you like highly quantitative research, feel free to reach out.
Jordan Kern, PhD
Assistant Professor in Coupled Natural-Human Systems
Department of Forestry and Environmental Resources
North Carolina State University
Campus Box 8008
Raleigh, NC 27695-8008 USA
email: jkern [at] ncsu [dot] edu