Xing Qiu, Ph.D.

I am a statistician and computational biologist working in the field of BigData analytics (high-throughput data analysis). I received my PhD in Mathematics (area: stochastic differential equations) from the University of Rochester in 2004. I joined the faculty of the Department of Biostatistics and Computational Biology at the University of Rochester in 2007. I have developed many statistical and computational methods for analyzing and integrating large-scale data with complex correlation structures such as various Omics data (gene expression, protein expression, microbiota abundance and diversity, etc) and medical image data (primarily structural MRI data). By now (2018), I have published 70 journal articles and book chapters, covering research topics such as Omics data pre-processing, hypothesis testing, multiple testing adjustment, functional data analysis, cluster analysis, network analysis, gene set enrichment analyses, and spatial statistical analysis for Diffusion Tensor Imaging data. Below please find some examples of my ongoing research projects:
• A Multi-step Integrative Analysis Pipeline for Multi-Omics Data
o Multi-site data integration based on novel batch effect removal method and cross-platform normalization method;
o A robust normalization and differential expression analysis pipeline (the super-delta method)
o A penalized multi-set CCA method for dimension reduction
o A computationally efficient linear mixed effects regression framework based on moment method, which can be used to estimate parameters and make correct inferences for correlated data with heterogeneous variance-covariance structure
o A robust meta-analysis framework to combine results from multiple studies
o Machine learning techniques for building predictive models based on features exacted from various datasets.
• Gene Set Enrichment Analysis with Capability of Defining Condition-specific Gene Sets
• Network Analysis Based on High-dimensional Ordinary Differential Equations and State Space Modeling
• Personalized Analyses for Longitudinal Imaging Data Based on Partial Differential Equations.
• Multiple Testing Procedure for Data with Rank-deficient Correlation Structure
• Using Lie Groups and Haar Measure in High-dimensional and Functional Data Analysis

I am also an active participant in collaborative research. Over the years, I have been involved in 20+ collaborative research projects, most of them are related to infectious diseases such as influenza, respiratory syncytial virus, and HIV. Currently, I am the Data Management, Informatics and Computational Biology Core Leader of the University of Rochester Respiratory Pathogens Research Center (RPRC); the Bioinformatics and Computational Biology Unit Leader of Center for AIDS Research (CFAR) at the University of Rochester.