Wen's research focuses on the use of spatiotemporal statistics and mathematical modeling to elucidate the distribution and transmission dynamics of infectious diseases, with particular attention to vector-borne diseases. She holds a PhD in Biostatistics and Biomathematics from the Sorbonne Université in Paris, France, and her doctoral research provides insights into the determinants of Lyme borreliosis incidence in metropolitan France. Her work integrated a variety of data sources, including disease surveillance data, remote sensing/environmental data, and anthropogenic data, within an integrated framework that employed a Bayesian two-part spatiotemporal modeling approach. As a postdoctoral researcher at Columbia, Wen is currently working to identify populations at highest risk for Lyme disease in the northeastern US by understanding how LD risk varies across urbanization gradients in relation to different ecological hazards, individual risk behaviors, and sociodemographic variables.
Postdoc