Di Shi
New Mexico State University, NM·Engineering
Floods, droughts and temperature extremes are colliding with aging energy infrastructure across the United States. Rural communities are hit hardest.
- Fields
Engineering
Earth & Environmental Science
Computer Science
- Topics
digital twin
artificial intelligence
energy systems
- Grants
- 1 known grant, through Aug 2028
What they work on
- Model multi-scale climate dynamics, including flooding, drought and temperature extremes, and link them to sociodemographic energy maps of three rural communities.
- Develop AI-driven digital twins, computer replicas of community energy systems, to test planning and operating strategies that improve efficiency, integrate renewables and build weather resilience.
- Run pilot studies in three communities with local co-development, and turn the results into open datasets, decision frameworks and interactive visual narratives.
More about the research
How can these communities plan energy systems that stay reliable, add renewable power, and remain affordable as the climate changes? This multi-jurisdiction project, called DigiCARES, tackles that question with AI-driven digital twins. A digital twin is a detailed computer model of a real system that can be used to test what-if scenarios before acting.
Why it matters
Rural communities facing extreme weather with aging grids need practical ways to plan energy systems. Digital twins that combine climate, energy and household data could help local planners and utilities test strategies before investing. These strategies could lower residents' energy costs, add renewable power, and keep power running through floods, droughts and heat or cold extremes. The approaches are designed to scale to other regions.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Ying Huang
North Dakota State University, ND·Engineering
Identify key risks to North Dakota's energy systems from extreme weather and cyber threats, and assess statewide research capacity and gaps, through capacity assessments and scenario development.
Avantika Gori
Rice University, TX·Engineering
Develop a flood-risk framework based on performance-based design, which judges solutions by how well they meet stated goals, and apply it in two rural Texas communities.
Lani Tsinnajinnie
University of New Mexico, NM·Earth & Environmental Science
Work with Indigenous and rural communities in New Mexico and Oklahoma, through a co-production process, to identify information needs about the land-water-air system under extreme weather.
The school
New Mexico State University: 2 labs on PI Pages, $143M a year on research, 90 research doctorates a year.
Reach out
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