My current research directions include: 1) designing novel statistical learning tools for integration of multiple heterogeneous sources and/or types of biomedical data; 2) detecting the latent structures of high dimensional biomedical data; 3) studying the tissue microenvironment and interactions of its cell components.
In the long run, my research interest is two-fold: one focused on development of novel statistical and machine learning techniques; and one focused on addressing important translational and biological questions, through data mining and quantitative modeling. Currently, for methodological research, I am developing algorithms to mine local low rank patterns in a high dimensional noisy data matrix, namely, biclustering and subspace clustering; for science driven research, I am interested in understanding how much epigenetic regulation, and its interaction with microenvironmental factors, contributes to transcriptional regulation of gene expression in cancer.