Area of research
Statistics and Probability · Computational Mechanics
Research interest
Research interests include Statistical Methods and Inference, Sparse and Compressive Sensing Techniques, Statistical Methods and Bayesian Inference, and Advanced Statistical Methods and Models.
H3K18 lactylation drives the progression of silica nanoparticles-induced pulmonary fibrosis via promoting macrophage M1 polarization
Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
A General Theory of Concave Regularization for High-Dimensional Sparse Estimation Problems
One Permutation Hashing
2012cited by 91position: last
Estimation and Inference with High-Dimensional Data
FRG: Collaborative Research: Dynamic Tensors: Statistical Methods, Theory, and Applications
Collaborative Research: Statistical Methods, Algorithms, and Theory for Large Tensors
SEMIPARAMETRIC INFERENCE WITH HIGH-DIMENSIONAL DATA
RI: Medium: Collaborative Research: Next-Generation Statistical Optimization Methods for Big Data Computing
BIGDATA: Small: DA: Statistical Machine Learning Methods for Scalable Data Analysis
STATISTICAL INFERENCE WITH HIGH-DIMENSIONAL DATA
Statistical Problems in Closed-Loop Diabetes Control
Statistical Methods and Theory in Some High-Dimensional Problems
Multi-Way Semilinear Methods with Applications to Microarray Data
Complex Datasets and Inverse Problems: Tomography, Networks, and Beyond; Rutgers University - New Brunswick, NJ; October 21-22, 2005
Statistical Models and Methods for Some Applied Problems
Mathematical Sciences: Presidential Young Investigator Award
Mathematical Sciences: Presidential Young Investigator