He obtained his PhD degree in Statistics at the University of Michigan and underwent postdoc training at Harvard University. He has more than 12 years of research experience in bioinformatics and computational biology. The major goal of Dr. Qin’s work is to provide analytical tools for the genetics and genomics research community. He has developed model-based methods to analyze high-throughput genomics and epigenomics data from ChIP-Seq, RNA-Seq, BS-seq and Hi-C experiments. His current research focuses to biological big data integration and mining. In addition to method development, he has collaborated extensively with biologists and clinicians to assist their efforts of identifying novel biological insights from their experimental data.