Faculty & Staff Directory
- Assistant Professor
PhD in Geography, Simon Fraser University, Canada
MSc in Geography, Simon Fraser University, Canada
BS in Environmental Studies, University of Waterloo, Canada
Taylor Anderson is an Assistant Professor in the Department of Geography and Geoinformation Science. She received her Ph.D. in Geography at Simon Fraser University, Canada. Her research lies at the intersection of Geographic Information Science (GISc) and urban health. Specifically, Dr. Anderson investigates the role of novel data-driven modeling and simulation approaches to better explain disease prevalence, predict future trajectories of disease, and improve public health response to diseases in both ecological and human systems. These approaches have been applied to complex problems of invasive species, infectious respiratory diseases, and non-communicable diseases.
Data-Driven Modeling to Improve Understanding of Human Behavior, Mobility, and Disease Spread
Dr. Anderson and team are investigating how the inclusion of how more realistic representations of human behavior can improve spatial agent-based models (ABM) of disease spread. The project focuses on the development of a conceptual data-driven modeling framework that acknowledges the spatial and temporal heterogeneity of human behavior and tightly-couples behavior to mobility, human interaction, and disease dynamics. The modeling framework will be transferrable and scalable so that it can be used to simulate a variety of diseases in different study areas.
The Role of the Urban Built Environment in Breast Cancer Mortality Health Disparities
Dr. Anderson and team are exploring the relationship between the urban built environment and breast cancer mortality health disparities in the United States. Health disparities are driven by complex and often interrelated factors. The built environment in which an individual is lives, including greenspace, health care providers, housing, walkability, healthy food choices, profoundly affects health and wellness. Despite recent commentaries that urge a better understanding of how
and why the environment matters to an individual’s health, the assessment of built environmental factors in relation to breast cancer survival is relatively unexplored.
RAPID: An Ensemble Approach to Combine Predictions from COVID-19 Simulations
Dr. Anderson and team are exploring the use machine learning approaches to combine predictions from a wide range of COVID-19 models, also called components, into what is called an ensemble. Ensemble models produce a single prediction that typically outperforms the predictions derived from its components. Different models produce radically different predictions with varying levels of uncertainty, creating confusion among policy makers and the public about the severity of the situation and how best to respond.
GGS 311 Introduction to Geographic Information Systems: students build hands on experience with cutting-edge geographic information systems (GIS) such as ArcGIS Pro and learn how to transform unorganized geographic data into meaningful geographic information.
GGS 563 Advanced Geographic Information Systems: students take a conceptual and practical dive into advanced relational spatial database management systems (PostgreSQL and PostGIS) and NoSQL database management systems (MongoDB and Neo4J).
GGS 531 Land-Use Modeling Techniques and Applications: students examine a range of different land use modeling approaches including statistical, machine learning, economic, cellular, and agent-based and develop hands on experience in developing a spatially explicit model of LULCC.
*Coming soon* GGS 590: Spatial Agent Based Modeling of Disease Spread: students will explore the use of agent-based models for simulating the spread of infectious diseases.
Please see: https://scholar.google.com/citations?user=PW-1fBQAAAAJ&hl=en&oi=ao for more information.