About Me

I am currently an Associate Research Scientist in Department of Environmental Health Sciences at Mailman School of Public Health, Columbia University. I study transmission dynamics of infectious diseases. Within this broad topic, I investigate how to use mathematical models to advance surveillance, forecasting and control of seasonal and emerging infectious agents. Specifically, I work on mathematical modeling, statistical inference and real-time forecast of disease spread at both population and individual levels. My recent works focus on the spatial spread of influenza, dengue and COVID-19, as well as the transmission of antimicrobial-resistant pathogens in healthcare systems.

Latest News

  • 04/01/2021 I will join the Department of Environmental Health Sciences at Mailman School of Public Health, Columbia University as a tenure-track assistant professor in fall 2021.
  • 02/09/2021 Our early work on undetected infections of SARS-CoV-2 is selected as one of the seven finalists of the AAAS Newcomb Cleveland Prize.
  • 01/29/2021 Our letter to editor "Social distancing remains key during vaccinations" is published online in Science.
  • 01/11/2021 New paper out in Nature Communications. Lack of a widespread surveillance network hampers accurate infectious disease forecasting. Here we provide a framework to optimize the selection of surveillance site locations and show that accurate forecasting of respiratory diseases for locations without surveillance is feasible.
  • 01/04/2021 Our paper "Multiscale mobility explains differential associations between the gross domestic product and COVID-19 transmission in Chinese cities" is published in Journal of Travel Medicine. In this letter, we find a Simpson’s paradox in the association between GDP and COVID-19 transmission in Chinese cities stratified by location. The differential associations in cities within and outside Hubei province can be explained by different patterns of short-range and long-range multiscale mobility from Wuhan to other cities.
  • 11/06/2020 Our study exploring the effect of non-pharmaceutical intervention on COVID-19 transmission in the US appears in Science Advances.
  • 08/28/2020 Our work on information diffusion "Realistic modelling of information spread using peer-to-peer diffusion patterns" is published online in Nature Human Behaviour. In this work, we develop a more realistic information cascade model that reproduces key structures of real-world diffusion trees in distinct social platforms by combining a peer-to-peer diffusion pattern with a correction for observational bias.
  • 04/23/2020 Together with colleagues at Mailman, we have developed three online tools to allow users to visualze the updated weekly projections of new COVID-19 cases, new infections, and available critical care beds in states and counties across the United States under a variety of social distancing and hospital response scenarios over a six-week period: (1) a data visualization tool that graph projections over time, (2) a mapping tool that charts county-level projections, and (3) animated maps.
  • 03/20/2020 The New York Times publishes an article "Without Urgent Action, Coronavirus Could Overwhelm U.S., Estimates Say" reporting our model projections of the COVID-19 outbreak in the US. Our results indicate that stringent control measures are required to reduce massive infections and flatten the epidemic curve.
  • 03/16/2020 Our research on the transmission dynamics of COVID-19 reveals that substantial undocumented infection fuels rapid spread of coronavirus in China. This study is published online in Science on March 16.