Data Science Institute

I am a GIScientist passionate about solving spatial decision making problems and understanding the role of uncertainty in spatial models, particularly for human-environment interactions. I did my Ph.D. in Geography in a joint doctoral program between UC Santa Barbara and San Diego State University. As a Ph.D. Student, I focused on  spatially explicit uncertainty and sensitivity analysis methods for land use models. At UMass, Amherst, as a researcher and educator, I have taught an array of GIS courses at various levels.  At Brown, I am eager to engage with diverse minds and continue to work with my colleagues on the complexities of human-environment dynamics.

How does your research, teaching, or other work relate to data or computational science?

My research focuses on the application of advanced spatial statistical methods, computational techniques, and spatial data analysis to address complex spatial problems in human-environment interaction. By leveraging large datasets, my work aims to uncover spatial patterns, uncertainty, and sensitivity in spatial models, as well as providing insights that can inform spatial decision making. 

In my teaching, I incorporate data science principles and tools to equip students with the skills necessary to analyze and interpret spatial data effectively. Courses I teach often include modules on programming, spatial statistics, and data visualization, all of which are essential components of data science. By integrating these elements into the curriculum, I prepare students to apply data science techniques in their future careers, particularly in the fields of environmental studies.