I am currently a postdoctoral research associate in the Department of Computer Science at Rensselaer Polytechnic Institute, as advised by Jianxi Gao. I obtained my Ph.D. degree in Data Science at the City University of Hong Kong in 2019, advised by Qingpeng Zhang.

 

My research focuses on improving healthcare operations during disaster events. Through developing data-driven modeling (Big Data/ML/AI) with network science theory, my research endeavors to improve public health, understand human behavior, and guide data-driven policymaking for disaster preparedness and response. Utilizing predictive modeling, complex systems analysis, and network optimization, my work has advanced insights into infectious disease spread (Nat.Commun.Phys'21, IEEETrans.Cybern'18), mobility patterns (ArXiv'23), and strengthening healthcare resilience to withstand and recover from global pandemics and climate-change disasters (Nat. Med'24).

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My research leverages terabytes and petabytes of data sourcing from various human mobility data and the COVID-19 Research Database (EHR data) to better understand human networks and behaviors at the center of societal challenges during disaster events. I have been awarded the Research Accelerator Grant from the Bill & Melinda Gates Foundation. I am also the referee for Journals like IEEE Transactions on Computational Social Systems, Physica A, and Scientific Reports.​​​

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Related links

• Healthcare System Resilience Estimates

• Mobility Models and Infectious Disease Spread