I am an expert in Bayesian biostatistical modeling for cancer genomics and computing for high-dimensional datasets. As PI or co-Investigator of research grants from NIH and NSF, I have developed novel Bayesian models for multi-domain, high-throughput biomedical studies. I have extensive experience with statistical computing to efficiently implement these methodologies for Big Data.
The primary focus of my research has been the development of broadly applicable, nonparametric statistical methodologies that are flexible because they avoid making unrealistic assumptions about the data features and permit nonlinear dependencies; scalable, because the procedures are capable of accommodating the ever-expanding massive, multiple-domain datasets, even on a modest computing budget; and most importantly, scientifically interpretable, because they are based on models that incorporate domain knowledge and provide meaningful answers to key scientific questions that motivate my work.
- Statistical methods