Associate Professor of Earth & Environmental Sciences
Associate Director for Research, Vanderbilt Climate Change Research Network
I work primarily at the intersection of natural science, social science, and public policy with a focus on coupled human-natural systems and on the ways in which scientific knowledge and uncertainty affect policy decisions about the environment.
My current work makes extensive use of agent-based models to simulate the ways that small changes in behavior at the individual level can add up to large-scale shifts at the level of the whole population, giving what is often referred to as “emergent phenomena.” These models have the potential to help us identify vulnerabilities to environmental stress and opportunities to promote sustainable adaptations.
My past research has included nonlinear dynamics and chaos, quantum optics, stratospheric photochemistry, electrocardiology, physical mechanisms of laser surgery, laser processing and analysis of semiconductors, laser-cooling of atomic ions, and high-precision atomic and molecular spectroscopy.
- Vandenbergh and Gilligan win the Morrison Prize for the most impactful scholarship on sustainability and the law. “Morrison Prize winners highlight importance of private action in battling climate change“
- “Betting and Belief: Prediction Markets and Attribution of Climate Change” by J.J. Nay, M. Van der Linden, and J.M. Gilligan. Accepted for Winter Simulation Conference 2016.
- “Dynamics of Individual and Collective Agricultural Adaptation to Water Scarcity,” by E.K. Burchfield and J.M. Gilligan. Accepted for Winter Simulation Conference 2016.
- “A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health,” by J.J. Nay, E. Burchfield, and J. Gilligan. Working paper.
- “Drought, Risk, and Institutional Politics in the American Southwest,” by D.J. Hess, C.A. Wold, J. Nay, S. Worland, J. Gilligan, and G.M. Hornberger. Sociological Forum, 31, 807-827 (2016).
- “Drinking water insecurity: water quality and access in coastal south-western Bangladesh,” by L. Benneyworth, J. Gilligan, J.C. Ayers, S. Goodbred, G. George, A. Carrico, Md.R. Karim, F. Akter, D. Fry, K. Donato, and B. Piya. Int. J. Environ. Health Res. advance online publication (2016).
- “Application of Machine Learning to the Prediction of Vegetation Health,” by E. Burchfield, J.J. Nay, and J. Gilligan, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 465-469 (2016).
- forecastVeg an open-source toolkit by J.J. Nay, E. Burchfield, and J. Gilligan for automatically downloading MODIS data, training a machine-learning tool, and forecasting vegetation health.
- “Employee Energy Benefits: What Are They and What Effect Do They Have on Employees?” by A. Maki, E. McKinney, M.P. Vandenbergh, M.A. Cohen, and J.M. Gilligan, working paper.
- “datafsm: Estimating Finite State Machine Models from Data” by John J. Nay and Jonathan M. Gilligan. Software Package. Comprehensive R Archive Network.