I am currently an UW Data Science Postdoctoral Fellow under the supervision of Prof. Bill Noble at Univerity of Washtington. My postdoctoral work focuses on developing machine learning methods for interpreting high-throughput genomic data sets with respect to 3D genome architecture, with a particular emphasis on embryonic development in mouse. Currently I am working on integration of imaging and sequencing data from visual cell sorting.
I got my Ph.D. in interdisciplinary statistics and operations research (INSTORE) with machine learning concentration at UNC at Chapel Hill in 2021. I was fortunate to be advised by both Prof. Jan Hannig and Prof. Yun Li. I obtained my M.S. in Statistics at UNC at the Chapel Hill in 2017 and my B.S. in mathematics and applied mathematics at Beijing University of Posts & Telecomunications in 2016.
Integration of imaging and sequencing data
Single-cell RNA sequencing
Bulk deconvolution, cell type specific analyses
Genome-wide association studies
Structual variation, copy number variation
Generalized ficuial inference
Deep fiducial inference and approximate fiduicial computation
First order approximate fiducial inference
HiC, HiChIP/PLAC-Seq chromatin 3D organization data