Runzi Wang, PhD, is a transdisciplinary researcher who studies change in natural and urban environments across space and over time, with the objective to drive positive change with ecological planning and design strategies. Combining technologies such as big data, machine learning, remote sensing, and spatial statistics, her primary research explores how land cover change and urban development pattern influence stream water quality and stormwater quality at the watershed basis, together with a variety of environmental, climatic and sociocultural factors. By enhancing the interpretability of machine learning in its application to landscape architecture, the most innovative part of her research is to uncover the nonlinear relationships between environmental, technological and sociocultural dimensions of landscape systems.

The focus areas of Runzi’s research include 1) Neighborhood-scale green infrastructure design optimization. 2) Regional-scale water quality management. 3) Continental-scale landscape change monitoring and projection. Runzi is also a landscape designer engaged in evidence-based landscape and urban design projects, with the focus on stormwater management. She integrates research with the teaching topics of ecological design studio, landscape analysis, and site engineering.