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Twitter: @lucine_zhong

Lu Zhong

I am currently a Postdoctoral Researcher Associate in the Department of Computer Science and Network Science and Technology Center at Rensselaer Polytechnic Institute. I obtained my Ph.D. degree in Data Science at the City University of Hong Kong in 2019. My current research is situated at the intersection of network science and data science. I concentrate on data-driven network modeling and optimization, with a particular emphasis on contagion processes and human mobility. Additionally, I have a keen interest in data-driven mechanistic modeling across various domains, with a specific focus on enhancing the resilience and adaptability of healthcare systems and global supply chain. My long-term goal is to bring network science and data science tools to the systems with managerial insights.


My research was supported by COVID-19 Research Accelerator Grants (Bill & Melinda Gates Foundation). I am serving as the referee for Journals like IEEE Transactions on Computational Social Systems, Communications Physics, and Scientific Reports.

Research Interests

  • Complex Network

  • Contagion Processes

  • Spatiotemporal Analysis

  • System Resilience/Adaptivity

Related website

  • 2023/10. Check our latest work on healthcare system resilience index and website

  • 2023/01. Check the special issue "Dynamics of Complex Networks" in Journal Entropy organized by Dr. Jianxi Gao, Dr. Lu Zhong, Dr. Bolesław Szymański, Dr. Xueming Liu.

  • 2022/12. Student James joined our project on the supply chain network.

  • 2022/10. Lu submitted her NIH K99/R00 application. 2023/03. Impact score top 40%. Many thanks to the advisory committee and all referees.

  • 2022/06. Undergraduate students Dimitri and Tarun joined our project on the healthcare system.

  • 2022/05. Lu participates in the Amazon AWS immersion training hosted by the Eshelman Institute, UNC.

  • 2022/05. New paper published in Humanities & Social Sciences CommunicationsVaccination and three non-pharmaceutical interventions determine the dynamics of COVID-19 at 381 metropolitan statistical areas in the US

  • 2022/05. New paper published in Chaos: Identifying the shifting sources predicts the dynamics of COVID-19 in US.

  • 2021/12. New paper published in Nature Communications Physics and recently represented on their cover art: Country distancing increase reveals the effectiveness of travel restrictions in stopping COVID-19 transmission.

  • 2021/07. Congratulations to Lu Zhong and Jianxi Gao for receiving funds from Bill & Melinda Gates Foundation, COVID-19 Research Database, and  Health Care Cost Institute.

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