Emily Hadley uses data science techniques to reveal insights and address societal challenges in a collaborative environment. She has experience in modeling, natural language processing, predictive analytics, and visualization, and expertise programming in Python and R. Prior to joining RTI in 2018, Emily served as an AmeriCorps college adviser in rural North Carolina, where she used data-driven techniques to build a college-bound culture. Her college advising work was featured in the New York Times in May 2017.
Preiss A, Hadley E, Jones K, Stoner MCD, Kery C, Baumgartner P, Bobashev G, Tenenbaum J, Carter C, Clement K, Rhea S. (2022). Incorporation of near-real-time hospital occupancy data to improve hospitalization forecast accuracy during the COVID-19 pandemic. Infectious Disease Modelling
Jones K, Hadley E, Preiss S, Lofgren ET, Rice DP, Stoner MCD, Rhea S, Adams JW. (2022). Estimate of undetected severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection in acute-care hospital settings using an individual-based microsimulation model. Infection control and hospital epidemiology
Hadley E, Rhea S, Jones K, Li L, Stoner M, Bobashev G. (2022). Enhancing the prediction of hospitalization from a COVID-19 agent-based model: A Bayesian method for model parameter estimation. PloS one, 17(3)
Endres-Dighe S, Jones K, Hadley E, Preiss A, Kery C, Stoner M, Eversole S, Rhea S. (2021). Lessons learned from the rapid development of a statewide simulation model for predicting COVID-19's impact on healthcare resources and capacity. PloS one, 16(11)