Yuchao Jiang, Principal Investigator
Assistant Professor, Department of Biostatistics, Gillings School of Global Public Health
Assistant Professor, Department of Genetics, School of Medicine
Member, Lineberger Comprehensive Cancer Center
University of North Carolina, Chapel Hill

News

Oct 2018: Yuchao gave a talk at AISC 2018.

Sept 2018: Tianyou Luo (first year Biostatistics PhD student) joined the lab as a graduate research assistant. Welcome Tianyou!

Aug 2018: Yuchao gave a talk at JSM 2018. (Link)

Jul 2018: The lab received funding from the Jayne Koskinas Ted Giovanis Foundation for Health and Policy for a multi-PI proposal titled “Single-Cell Dynamics for Precision Medicine in Cancer”, joint with Stephanie Hicks from Johns Hopkins and Sahand Hormoz from Harvard.

Jun 2018: Yuchao was selected to attend the BD2K Innovation Lab on Single Cell Dynamics at Bend, OR. (Link)

Feb 2018: MARATHON is online at Bioinformatics. (Html, GitHub)

Jan 2018: The lab received the UNC Lineberger Developmental Award. (News)

Dec 2017: Biostatistics Ph.D. candidates Rujin Wang and Meichen Dong joined the lab. Welcome!

Nov 2017: Gene Urrutia joined the lab as a postdoc fellow. Welcome Gene!

Oct 2017: Yuchao gave a talk at the Bioinformatics and Computational Biology Colloquium at UNC-CH. (Link)

Background

I obtained my Ph.D. in Genomics and Computational Biology from the University of Pennsylvania in 2017 working with Dr. Nancy R. Zhang (advisor) and Dr. Mingyao Li. I obtained my M.A. in Statistics from the University of Pennsylvania in 2014 and my B.S. from Cornell University in 2012. I started as an Assistant Professor of Biostatistics and Genetics at UNC Chapel Hill in 2017.

Research

The Jiang Lab’s primary research interests lie in statistical modeling, method development and data analysis in genetics and genomics. Our current research is focused on developing statistical methods and computational algorithms to better utilize and analyze different types of next-generation sequencing data under various setting, with application to data from large-scale cohort studies of human health and disease. Special focus is on single-cell transcriptomics, single-cell epigenomics, cancer genomics, tumor phylogeny, data normalization, and copy number variation detection.