avatar

Jianbin Tan

Postdoctoral Associate
Duke University
jianbin.tan@duke.edu


Welcome to Jianbin's homepage!

I am currently a Postdoctoral Associate in the Department of Biostatistics & Bioinformatics, Duke University, supervised by Prof. Anru Zhang and Prof. Pixu Shi. I received my PhD in Statistics from Sun Yat-sen University in 2023, advised by Prof. Hui Huang. I was a visiting student working with Prof. Xueqin Wang in the School of Management, USTC, in 2022.

My research interests lie in statistical learning for data with dynamic-, longitudinal-, or trajectory- based structures. Such data often exhibit complicated intrinsic mechanisms, dependencies, and heterogeneity, as well as challenges such as noise, irregular sampling, and high- or even infinite-dimensionality. To address these, I focus on developing new methodologies for statistical learning of functions, flows, and differential equations, supporting effective analysis in biology, health, epidemiology, and environmental science.

Research Paper

  1. Preprint
    Smooth flow matching
    Jianbin Tan, and Anru Zhang.
    Preprint.
    View on Arxiv
  2. Preprint
    Sparse equation matching: a derivative-free learning for general-order dynamical systems
    Jiaqiang Li, Jianbin Tan, and Xueqin Wang.
    Preprint.
    View on Arxiv
  3. Preprint
    A unified principal components analysis of stationary functional time series
    Zerui Guo, Jianbin Tan (joint first authorship), and Hui Huang.
    Preprint.
    View on Arxiv
  4. A frequency-domain approach for integrating multiple functional time series
    Zerui Guo, Jianbin Tan, and Hui Huang.
  5. JASA
    A singular value decomposition framework for learning with heterogeneous functional data
    Jianbin Tan, Pixu Shi, and Anru Zhang.
    under minor revision at Journal of the American Statistical Association.
    View on GitHub    View on Arxiv
  6. JBI
    Integrated analysis for electronic health records with structured and sporadic missingness
    Jianbin Tan, Yan Zhang, Chuan Hong, T. Tony Cai, Tianxi Cai, and Anru Zhang.
    Journal of Biomedical Informatics, 2025.
    View on GitHub    View on Arxiv
  7. AOAS
    Functional clustering for longitudinal associations between social determinants of health and stroke mortality in the U.S.
    Fangzhi Luo, Jianbin Tan (joint first authorship), Donglan Zhang, Hui Huang, and Ye Shen.
    Annals of Applied Statistics, 2025.
    View on GitHub    View on Arxiv
  8. JRSSB
    Green’s matching: an efficient approach to parameter estimation in complex dynamic systems
    Jianbin Tan, Guoyu Zhang, Xueqin Wang, Hui Huang, and Fang Yao.
    Journal of the Royal Statistical Society, Series B (Statistical Methodology), 2024.
    View on GitHub    View on Arxiv
  9. JASA
    Graphical principal component analysis of multivariate functional time series
    Jianbin Tan, Decai Liang, Yongtao Guan, and Hui Huang.
    Journal of the American Statistical Association, 2024.
    View on GitHub   View on Arxiv  
  10. BIOM
    Age-related model for estimating the symptomatic and asymptomatic transmissibility of COVID-19 patients
    Jianbin Tan, Ye Shen, Yang Ge, Leonardo Martinez, and Hui Huang.
    Biometrics, 2023.
    View on GitHub
  11. I&E
    Social mixing and network characteristics of COVID-19 patients before and after widespread interventions: A population-based study
    Yuncong He, Leonardo Martinez, Yang Ge, Yan Feng, Yewen Chen, Jianbin Tan, Adrianna Westbrook, Changwei Li, Wei Cheng, Feng Ling, Huimin Cheng, Shushan Wu, Wenxuan Zhong, Andreas Handel, Hui Huang, Jimin Sun, and Ye Shen.
    Epidemiology & Infection, 2023.
    View on GitHub
  12. I&E
    Transmission roles of symptomatic and asymptomatic COVID-19 cases: a modelling study
    Jianbin Tan, Yang Ge, Leonardo Martinez, Jimin Sun, Changwei Li, Adrianna Westbrook, Enfu Chen, Jinren Pan, Yang Li, Wei Cheng, Feng Ling, Zhiping Chen, Ye Shen, and Hui Huang.
    Epidemiology & Infection, 2022.
    View on medRxiv
  13. JASA
    The effects of stringent and mild interventions for coronavirus pandemic
    Ting Tian, Jianbin Tan (joint first authorship), Wenxiang Luo, Yukang Jiang, Minqiong Chen, Songpan Yang, Canhong Wen, Wenliang Pan, and Xueqin Wang.
    Journal of the American Statistical Association, 2021.
    View on GitHub
  14. JDS
    Evaluate the risk of resumption of business for the states of New York, New Jersey and Connecticut via a pre-symptomatic and asymptomatic transmission model of COVID-19
    Ting Tian, Jianbin Tan (joint first authorship), Yukang Jiang, Xueqin Wang, and Heping Zhang.
    Journal of Data Science, 2021.
    View on GitHub    View on medRxiv