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Cornell University

Charles Research Group

Community-Building through Computational Methods

Research

The Charles lab works to analyze and design systems that expand past traditional engineering (technological systems) to investigate the challenges and opportunities that are inherently connected to adding variables within the expanded system boundaries. We are particularly interested in the vital role that landscapes can play in addressing complex sustainability challenges and how ecosystem services promote well-being to the human population. The dynamic interactions between these social, ecological and technological elements across space and time continue to provide interesting research challenges in the modeling, simulation, and optimization of such systems.

The Social-Ecological-Technological system (SETs) describing interactions between people, place, and industry.
The Social-Ecological-Technological system (SETs) describing interactions between people, place, and industry. The focus of conventional engineering is outlined by the dashed line system boundary.

Understanding the limits of computational approaches, the Charles lab is also committed to working with communities of practice (non-academic communities) to explore how computational results can lead to transformed behavior, practice, and policy. Particularly, we are interested in building relationships and collaborating with Indigenous Nations as we can explore the interface of multiple knowledge systems (i.e. institutionalized science and Indigenous knowledge) and work directly with community leaders or Tribal governments to execute any community-determined actionable steps. These relationships also lead to research projects that aim to meet community-identified needs, broadening the applications of the computational approaches developed in the lab.

Current projects include:

  • Downscaling integrated assessment models to explore the impacts of climate change on the economies of geographically small-scale governments, like those of Indigenous Nations
  • Spatially-explicit nature-based solutions (NBS) frameworks focused on climate mitigation and public health simultaneously
  • Participatory System Dynamics Modeling (PSDM) exploring the impacts of race in food systems
  • Participatory AI: Building a research atlas with community-defined classifications for Indigenous populations in Nunavik (Northern Quebec)
  • Analyzing the impacts on current Indigenous food systems in the context of dispossession and the endowments of Land Grant Universities through the Morrill Act
  • Re-evaluating the sustainability of computing through the perspective of the Food-Energy-Water (FEW) nexus