John Ringland
PhD
Associate Professor
Research Interests
Applied mathematics, bifurcation theory, mathematical modeling, computational mathematics.
Education
PhD, University of Texas, Austin
Research Summary
Applied mathematics, bifurcation theory, mathematical modeling, computational mathematics.
Professor Ringland works in the qualitative and quantitative analysis of deterministic and stochastic dynamical systems.
Selected Publications
Automated Survey of Selected Common Plant Species in Thai Homegardens Using Google Street View Imagery and a Deep Neural Network, John Ringland, Martha Bohm, So-Ra Baek, Matthew Eichhorn. Earth Science Informatics, 14, 179–191, 2021.
Characterization of food cultivation along roadside transects with Google Street View imagery and deep learning, John Ringland, Martha Bohm, So-Ra Baek, Computers and Electronics in Agriculture, 158, 36-50, 2019.
Boundaries of Sustainability in Simple and Elaborate Models of Agricultural Pest Control with a Pesticide and a Nontoxic Refuge, J. Mohammed-Awel, J. Bantle, A. Festinger, H. Jo, R. Klafehn, J. Ringland, J. Biol. Dyn., 6, 80-95, 2012.
Analysis of Sustainable Pest Control Using a Pesticide and a Screened Refuge, J. Ringland and P. George, Evolutionary Applications, 4, 459-470, 2011.
A Situation in which a Local Nontoxic Refuge Promotes Pest Resistance To Toxic Crops, Jemal Mohammed-Awel, Karen Kopecky, John Ringland, Theoretical Population Biology, 71, 2, 131-146, 2007.
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John Ringland