Nathan Brugnone, PhD

Nathan Brugnone

CSUS - Complex {Adaptive} Systems, Computational Mathematics, Social-Ecological Systems Modeling, Machine Learning

Program: Community Sustainability (CSUS), Computational Math, Science, & Engineering (CMSE)

Hometown: Lansing/Brighton, Ml, USA

Advisor: Robert Richardson (CSUS) & Matthew Hirn (CMSE)

Nathan Brugnone is a doctoral student pursuing a dual PhD in Community Sustainability (CSUS) and in Computational Mathematics, Science, and Engineering (CMSE) at Michigan State University. His research combines applied and computational harmonic analysis, graph theory, and data science in the study of complex social-ecological systems. His areas of interest include the development of computational tools to support agricultural sustainability, the formalization of conceptions of emergence in complex systems models (e.g., agent-based models [ABM]), and the development of mathematically provable guarantees on methods for such pursuits. Nathan earned an MS in Agriculture from Washington State University.

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