Research and Teaching Interests

Dr. Xiao's research mainly focuses on the development and application of powerful and efficient statistical methods for high throughput genetics and genomics data, driven by the challenges arising from the modern biotechnologies such as next-generation sequencing and single cell sequencing. Dr. Xiao is also interested in exploring the advantages of machine learning methods and approaches in public health related outcomes, especially in handling high throughput data. Dr. Xiao specifically works on the next generation chromosomal copy number variation detection, integrative analysis of ‘omics’ data (such as SNP, methylation and expression data), and neuroimaging genetic data analysis. Much of her effort is motivated by ongoing collaboration projects in cancer, aging and other public health related outcomes. Her ultimate research goal to provide efficient statistical tools to integrate the genetic/genomic data into practice of precision medicine. Dr. Xiao is teaching courses including Intermediate of Biostatistics, Categorical Data Analysis and Statistical Genetics.