Jie Peng, Ph.D.

Jie Peng

Professor
Vice-Chair for Graduate Affairs

  • Statistics
My name only
4216 Mathematical Sciences Building
One Shields Avenue, Davis CA 95616

Education

  • Stanford University, Ph.D

Research Interests

  • Graphical Models
  • High Dimension Inference
  • Functional Data Analysis
  • Statistical Genomics
  • Neuroimaging

Selected Works

  • Yan H., Carmichael O., Paul D., and J. Peng. Estimating fiber orientation distribution from diffusion MRI with spherical needlets (2018). To appear on Medical Imaging Analysis. [arXiv:1612.07439]
  • Zhou S., Paul D., and J. Peng. Modeling subject-specific nonautonomous dynamics (2018). Statistica Sinica 28 (2018), 423-447. [pdf]
  • Choi Y., Coram M., J. Peng, and Tang H. A Poisson Log-Normal model for constructing gene covariation network using RNA-seq data (2017).  Journal of Computational Biology, 24(7):721-731. [pdf]
  • An C., Ichihashi Y., J. Peng, Sinha N.R., Hagiwara N. (2016). Transcriptome dynamics and potential roles of Sox6 in the postnatal heart.  PloS One 11(11): e0166574. [html]
  • Paul D., J. Peng, and P. Burman. Nonparametric estimation of dynamics of monotone trajectories (2016).  The Annals of Statistics, Vol. 44, No. 6, 2401-2432. [pdf]
  • Wong, R.K.W., T.C.M. Lee, D. Paul, and J. Peng. Rejoinder: Fiber direction estimation, smoothing and tracking in diffusion MRI (2016). The Annals of Applied Statistics, 10(3): 1166-1169. [pdf]
Publications
  • Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic data of ovarian cancer
    Journal Article | Chowdhury, S., Ferri-Borgogno, S., Yang, P., Wang, W., Peng, J., Mok, S., Wang, P. Briefings in Bioinformatics, 26, bbaf085. 10.1093/bib/bbaf085
  • ESTIMATING FIBER ORIENTATION DISTRIBUTION WITH APPLICATION TO STUDY BRAIN LATERALIZATION USING HCP D-MRI DATA.
    Journal Article | Hwang, S., Lee, T., Paul, D., Peng, J. The Annals of Applied Statistics, 18, 100-124. 10.1214/23-aoas1781
  • Testing General Linear Hypotheses Under a High-Dimensional Multivariate Regression Model with Spiked Noise Covariance
    Journal Article | Li, H., Aue, A., Paul, D., Peng, J. Journal of the American Statistical Association, 119, 2799-2810. 10.1080/01621459.2023.2278825
  • DAGBagM: learning directed acyclic graphs of mixed variables with an application to identify protein biomarkers for treatment response in ovarian cancer
    Journal Article | Chowdhury, S., Wang, R., Yu, Q., Huntoon, C., Karnitz, L., Kaufmann, S., Gygi, S., Birrer, M., Paulovich, A., Peng, J., Wang, P. BMC Bioinformatics, 23, 321. 10.1186/s12859-022-04864-y
  • An adaptable generalization of Hotelling’s $T^{2}$ test in high dimension
    Journal Article | Li, H., Aue, A., Paul, D., Peng, J., Wang, P. The Annals of Statistics, 48, 1815-1847. 10.1214/19-aos1869
  • See publications and more on Aggie Experts: https://experts.ucdavis.edu/expert/K49GqrkD