Novel Machine Learning Methods for Genomic Data Analysis

Efficient quantification of pattern similarity between spatial genomics and cell morphology

Association Study between Diseases and Human Tissue-Specific Epigenomes

Developing enrichment analyzing methods at sub-cell type level to generate novel insights on complex disease pathogenesis

Statistical Methods for Analyzing Microbiome Data

Disease Risk annotation of Genomic and Epigenomic Variants using Machine Learning Approaches

Characterizing the Developmental Trajectories for Cerebellar Volumes via Penalized Splines and Derivative Analysis

EDClust: An EM-MM hybrid method for cell clustering in population-level single cell RNA sequencing

Statistical Modeling and Learning in Single Cell RNA Sequencing Data