Jing Huang PhD
Jing Huang (she/her) is a faculty member at PolicyLab at Children’s Hospital of Philadelphia, an assistant professor of biostatistics in the Department of Biostatistics, Epidemiology and Informatics, and a senior scholar in the Center for Clinical Epidemiology and Biostatistics at the University of Pennsylvania’s Perelman School of Medicine. Dr. Huang’s research focuses on methodology and software development to understand the dynamics of disease activities and inform control policies using longitudinal health data. She is currently a principal investigator of National Institutes of Health (NIH) and Patient-Centered Outcomes Research Institute (PCORI) funded projects. One project is in methods and software for characterizing disease trajectory and improving treatment in pediatric Crohn's disease, and the other project is in methods and software for data integration in a Clinical Research Network.
Dr. Huang is one of the lead investigators on PolicyLab’s COVID-19 forecasting model, known as “COVID-Lab: Mapping COVID-19 In Your Community,” which tracked coronavirus transmission and test positivity rates across all U.S. counties, and provided four-week case incidence forecasts for more than 800 counties with active outbreaks between April 2020 and May 2021. Dr. Huang and her collaborators have received national attention for this unique project, which they have used to advise the White House Coronavirus Task Force, governors, state public health officials and Philadelphia leaders on emerging hotspots and local strategies for reducing the spread of the virus.
Dr. Huang is a mathematical and statistical modeler. She has worked on several exciting research areas, including dynamic intervention-based on mobile health data, knowledge discovery using electronic health records data, pharmacovigilance using safety reports from the Food Drug Administration (FDA) and Centers for Disease Control and Prevention (CDC) funded post-market surveillance systems, and evidence generation in pediatric distributed research networks.