Research Interests

• Statistical machine learning for high dimensional data

• Bayesian sparse learning and its applications in cancer genomics

• High/Ultra-high dimensional robust variable selections

• Integrative analysis of cancer genomics data from multiple platforms

• Large scale (convex and non-convex) optimizations in statistical genomics and bioinformatics

• Adaptive Bayesian prediction of patient recruitment in clinical trials.

Funding

• PI. (with Co-PI W. Wang).  Integrative Lipid - Environment Analysis for Cancer Prevention Studies.  Innovative Research Award. Johnson Cancer Research Center.  2017 - 2018.

• Travel award for the annual Arthur M. Sackler Colloquium at the National Academy of Sciences. 2017.

• PI.  Robust Network Analysis of High Dimensional Genomics Data for Cancer Prognosis. K State Faculty Enhancement Award. 2017 - 2018.

• PI. Summer workshop on Statistical Machine Learning for High-dimensional Data. 2018. Co-sponsored by Shell Oil.

• Co-PI. HPV Oncogenes Dysregulate Translesion Synthesis. 05/2020 - 04/2023. NIH R15.

• PI. (with Co-PI W. Wang).  Bayesian Analysis of Longitudinal Lipidomics Data in Cancer Prevention Studies. Innovative Research Award. Johnson Cancer Research Center.  12/2021 - 05/2023.