Dimensionality reduction for classification with high-dimensional data 

Generalized linear discriminant analysis for high-dimensional genomic data with external information 

Feature selection in high-dimensional modeling with thresholded regression 

Sparseness in functional data analysis 

Robust feature selection with penalized regression in imbalanced high dimensional data 

Latent unknown clustering with integrated data (LUCID) 

High-dimensional feature selection and its applications 

Essays on high-dimensional econometric models 

Information granulation and dimensionality reduction of seismic vibration monitoring data using orthonormal discrete wavelet transform for possible application to data mining, 2003 

Prediction and feature selection with regularized regression in integrative genomics 

Statistical learning in High Dimensions: Interpretability, inference and applications 

Reproducible large-scale inference in high-dimensional nonlinear models 

Efficient machine learning techniques for low- and high-dimensional data sources 

High-dimensional regression for gene-environment interactions 

Stochastic optimization in high dimension 

Hierarchical regularized regression for incorporation of external data in high-dimensional models 

Incorporating prior knowledge into regularized regression 

Statistical analysis of high-throughput genomic data 

Improved computational and statistical guarantees for high dimensional linear regression 

Numerical methods for high-dimensional path-dependent PDEs driven by stochastic Volterra integral equations 

Essays on factor in high-dimensional regression settings 

Zero-dimensional and one-dimensional nanostructured materials for application in photovoltaic cells 

Integrative analysis of multi-view data with applications in epidemiology 

Magnetization study of two dimensional helium three 

Transmission tomography for high contrast media based on sparse data