Welcome to My Homepage

My research mainly falls into the following areas: object oriented data analysis, statistics on manifolds, and model selection. My primary research centers on developing new mathematical and statistical methods to solve many problems from various scientific research fields.

Object oriented data, such as tree-structured data, random graphs, manifold data and curve data, are frequently collected. In object oriented data analysis, Many problems were motivated by data from neuro-image which can be represented by a set of tree-structured objects. The fundamental properties of the topological structures were studied. Recently, I am particularly interested in the problem of modeling tree-structured data to explain the relationship between tree-structured covariates and numerical response, and/or between numerical covariates and tree-structured response.

In the topic of manifold learning, I considered the problem of manifold recovery and curvilinear feature extraction, and demonstrated the connection between nonlinear latent structure analysis and locally linear embedding.

In my recent research interest in model selection, two different problems were considered: Hellinger distance based model selection, and regularized spatial linear regression.


B.S., Nankai University, Tianjin, China

Ph.D., University of North Carolina, Chapel Hill

Current Research Interests

Object Oriented Data Analysis

Spatial Statistics

Information Fusion

Statistical Analysis on Networks

Computational Neuroscience

Contact Information

216 Statistics Building
Department of Statistics
Colorado State University
Fort Collins, CO80523

Email: wanghn@stat.colostate.edu
Voice: 970-491-2449

Acknowlegement of Support

My research has been supported by NSF grants DMS-0706761, DMS-0854903, DMS-1106975, DMS-1521746 and DMS-1737795 as well as grants with other collaborators.