Meng Li

Visiting Assistant Professor

Department of Statistical Science
Duke University, Box 90251
Durham, NC 27708-0251 USA
Email: at

     Research             Papers              Software              Teaching             Curriculum Vitae

Research interests
  • Multiscale modelling
  • Image analysis
  • Network analysis
  • Online algorithms
  • Functional data analysis
  • Nonparametric Bayes

Papers and preprints

Li, M. and Dunson, D. (2017). Framework for Probabilistic Inferences from Imperfect Models. Submitted. arXiv:1611.01241

Li, M.
, Wang, K., Maity, A. and Staicu, A.M. (2016+). Inference in Functional Linear Quantile Regression. Under revision. arXiv:1602.08793, R Code

Li, M. and Schwartzman, A. (2016+). Standardization of Multivariate Gaussian Mixture Models for Background Adjustment of PET Images in Brain Oncology. Under revision.

Syring N. and Li, M. (2017). BayesBD: An R Package for Bayesian Inference on Image Boundaries. Submitted. arXiv:1612.04271

Li, M. and Ghosal, S.(2016). Bayesian Detection of Image BoundariesAnnals of Statistics, To appear. arXiv:1508.05847.

Li, M., Staicu, A.M. and Bondell, H. (2015). Incorporating Covariates in Skewed Functional Data Models. Biostatistics, 16(3):413-426.

Li, M. and Ghosal, S.(2015). Fast Translation Invariant Multiscale Image Denoising. IEEE Transactions on Image Processing, 12(24), 4876-4887.

Li, M. and Ghosal, S.(2014). Bayesian Multiscale Smoothing of Gaussian Noised Images. Bayesian Analysis, 9(3), 733-758.

Li, M. (2014). Prediction of user's demographics based on web usage mining - personalized advertisement. Technical Report - Summer Intern at MaxPoint.


Li, M. and Schwartzman A. (2016), RB-SGMM-BA, Matlab toolbox for robust estimation of spatial Gaussian mixture model and background adjustment.

Syring, N and Li, M. (2016), BayesBD (3rd version, v1.1), R package for Bayesian boundary detection in images using Gaussian process priors.

Li, M.
, Staicu, A.M. and Bondell, H. (2014), cSFM, R package to model skewed functional data when considering covariates via a copula-based approach.

Li, M. (2014),  Fast Translation Invariant Multiscale Image Denoising (2D, 3D, Poisson, Gaussian images), Matlab toolbox to implement fast translatoin invariant algorithms for general multiscale image denoising.

Li, M. (2014), Bayesian Multiscale Smoothing for d-dimensional Gaussian Noised Images, Matlab toolbox for 3D image denoising.

Li, M. (2014), Bayesian Multiscale Smoothing for 2-dimensional Gaussian Noised Images, Matlab toolbox for 2D image denoising.


Current:  STA250/MTH 342 - Statistics


STA250/MTH 342 - Statistics (Instructor)
Spring 2016 at Duke DSS

STA 611 Introduction to Mathematical Statistics (Instructor)
Fall 2015, 2016 at Duke DSS

ST 311 Introduction to Statistics (Instructor)
Fall 2012, Spring 2013, Summer 2013 at NC State

ST 512 Experimental Statistics II (Lab Instructor)
Summer 2012, Fall 2011 at NC State

ST 746 Stochastic Process (Software Assistant)
Spring 2012 at NC State

ST 370 Introduction to Statistics and Probability for Engineers (Lab TA)
Spring 2012 at NC State