I’m a computational health scientist, working between clinical informatics and epidemiology.
On the clinical side, I apply causal inference, statistical learning, and geospatial analysis to large-scale clinical, demographic, and geographic data. This includes comparative effectiveness research: randomized and pragmatic trials where feasible, target trial emulation where a trial is not, and implementation science to carry the evidence into practice.
On the population health side, I combine field epidemiology methods with survey data, syndromic surveillance, and mobility data for humanitarian emergency response, in the war in Syria, the 2018 Kerala floods, the Rohingya refugee crisis in Cox’s Bazar, and climate-driven displacement in coastal North Carolina.
My dissertation links spatiotemporal climate data with individual-level health data, and uses the linked records to quantify the cumulative burden of climate extremes on population displacement, disease, and death, with movement as the pathway connecting exposure to health.
As a Graduate Research Assistant with
Dr. Emily Pfaff, I apply causal inference within a target trial framework to assess the comparative effectiveness of treatments in national multi-site EHR data. The same work applies statistical learning for automated cohort identification and computable phenotyping.
With Dr. Barbara Entwisle at the Carolina Population Center, I study what electronic health record address histories can measure about residential mobility, including movement driven by displacement.