Sen Pei

Sen Pei

Sen Pei

Associate Research Scientist
Environmental Heath Sciences


722 West 168th Street, Room 1104C
New York NY 10032
Website address: Email:


Dr. Sen Pei is interested in mathematical modeling, statistical inference and real-time forecast of infectious disease spread. With expertise in applied mathematics, statistics and network science, he studies the transmission dynamics of seasonal and emerging infectious diseases at both population and individual levels. Using dynamical models informed by empirical data, his recent work involves the development of real-time forecast systems to predict the spatial spread of influenza and dengue, as well as statistical methods to infer nosocomial transmission and asymptomatic carriage of antibiotic-resistant bacteria. In addition, he investigates how the nonlinear model dynamics can be harnessed to improve disease surveillance and forecast.



PhD, 2015, Beihang University & City College of New York
BS, 2010, Beihang University

Areas of Expertise

Bayesian Methods, Systems Science, Epidemics, Infectious Disease

Select Publications

Pei, S., Cane, M. A., & Shaman, J. (2019). Predictability in process-based ensemble forecast of influenza. PLoS Computational Biology, 15(2), e1006783.
Pei, S., Morone, F., Liljeros, F., Makse, H., & Shaman, J. L. (2018). Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus. eLife, 7, e40977.
Pei, S., Kandula, S., Yang, W., & Shaman, J. (2018). Forecasting the spatial transmission of influenza in the United States. Proceedings of the National Academy of Sciences, 115(11), 2752-2757.
Kandula, S., Yamana, T., Pei, S., Yang, W., Morita, H., & Shaman, J. (2018). Evaluation of mechanistic and statistical methods in forecasting influenza-like illness. Journal of the Royal Society Interface, 15(144), 20180174.
Fu, C., Dong, Z., Shen, J., Yang, Z., Liao, Y., Hu, W., Pei, S., & Shaman, J. (2018). Rotavirus gastroenteritis infection among children vaccinated and unvaccinated with rotavirus vaccine in southern China: a population-based assessment. JAMA Network Open, 1(4), e181382-e181382.
Pei, S., Morone, F., & Makse, H. A. (2018). Theories for influencer identification in complex networks. In Complex Spreading Phenomena in Social Systems (pp. 125-148). Springer.
Zhang, R., & Pei, S. (2018). Dynamic range maximization in excitable networks. Chaos: An Interdisciplinary Journal of Nonlinear Science, 28(1), 013103.
Pei, S., & Shaman, J. (2017). Counteracting structural errors in ensemble forecast of influenza outbreaks. Nature Communications, 8(1), 925.
Pei, S., Teng, X., Shaman, J., Morone, F., & Makse, H. A. (2017). Efficient collective influence maximization in cascading processes with first-order transitions. Scientific Reports, 7, 45240.
Pei, S., Muchnik, L., Andrade Jr, J. S., Zheng, Z., & Makse, H. A. (2014). Searching for superspreaders of information in real-world social media. Scientific Reports, 4, 5547.

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