Marina Sundiang is a Postdoctoral Associate in the Food Systems & Global Change (FSGC) research group, housed in Cornell CALS Department of Global Development. Her research focuses on the emergent properties of interconnected complex systems using computational tools and real-world data. Now a member of the EAT-Lancet 2.0 Modeling Workstream, Marina leverages her transdisciplinary background to understand the complexities of food systems.
Before joining FSGC, Marina completed her doctorate in Computational Neuroscience at the University of Chicago where she investigated the temporal dynamics of biological neural networks during goal-directed behavior. Her previous work highlighted that models that incorporate interactions between system components, rather than treating them as independent, provide a more nuanced perspective.