Welcome!

I am currently a postdoctoral research scholar at Department of Biostatistics and Epidemiology, University of Pennsylvania, under the supervision of Prof. Wensheng Guo and Prof. Wei (Peter) Yang. I received B.S. in Statistics from Peking University, and Ph.D. in Statistics from School of Mathematics and Statistics, the University of Melbourne, under the supervision of Prof. Aurore Delaigle. I was a postdoctoral research scholar at Fa­kul­tät für Ma­the­ma­tik, Ruhr-Uni­ver­si­tät Bo­chum, under the supervision of Prof. Holger Dette, and a postdoctoral research scholar at Department of Statistics, Harvard University, under the supervision of Prof. Zheng (Tracy) Ke. I am honored to receive the 2025 IMS New Researcher Travel Award.

Email: jttang[at]upenn.edu

Research interests

  • Methodology: Network data analysis, functional data analysis, longitudinal data analysis, nonparametric and semiparametric statistics, measurement errors.
  • Theory: Asymptotic theory, self-normalization, reproducing kernel Hilbert space (RKHS), minimax theory.
  • Applications: Large cohort studies, cardiovascular disease, chronic kidney disease, electronic health record (EHR) data.

Academic appointment

  • 2024/07 - now: Postdoctoral research scholar, Department of Biostatistics and Epidemiology, University of Pennsylvania, USA.
  • 2023/02 - 2024/07: Postdoctoral research scholar, Department of Statistics, Harvard University, USA.
  • 2021 - 2023: Postdoctoral research scholar, Fakultät für Mathematik, Ruhr–Universität Bochum, Germany.

Education

  • 2016 - 2021: Ph.D. in Statistics, the University of Melbourne, Australia.
  • 2012 - 2016: B.S. in Statistics, Peking University, China

Publications

(* indicates alphabetical authorship)

  • Jin, J., Ke, T., Tang, J.* and Wang, J. (2025). [DOI] [arxiv] [code and supplement]
    Network goodness-of-fit for the block-model family.
    Journal of the American Statistical Association (Theory and Methods), to appear.
    ★ Jiajun Tang received 2025 IMS New Researcher Travel Awards.

  • Dette, H. and Tang, J.* (2025)
    New energy distances for statistical inference on infinite dimensional Hilbert spaces without moment conditions. [arxiv]
    Bernoulli, to appear.

  • Tang, J. and Dette, H. (2025).
    Simultaneous semiparametric inference for single-index models. [DOI] [arxiv]
    Bernoulli, 31, 2962-2986.

  • Jin, J., Ke, T., Moryoussef, G., Tang, J.* and Wang, J. (2024).
    Improved algorithm and bounds for successive projection. [OpenReview] [arxiv]
    International Conference on Learning Representations (ICLR).

  • Dette, H. and Tang, J.* (2024)
    Statistical inference for function-on-function linear regression. [DOI] [arxiv]
    Bernoulli, 30, 304-331.

  • Dette, H. and Tang, J.* (2024)
    An RKHS approach for pivotal inference in functional linear regression. [DOI] [code]
    Statistica Sinica, 34, 1521-1543.

  • Dette, H. and Tang, J.* (2024)
    Pivotal inference for function-on-function linear regression via self normalization. [DOI]
    Recent Advances in Econometrics and Statistics: Festschrift in Honour of Marc Hallin, 557-574.

Ph.D. dissertation