Yinqiu is broadly interested in developing theory and methodology for analyzing large-scale and complex-structured data to address scientific problems arising from interdisciplinary studies. Her current research interests include high-dimensional and large-scale statistical inference, rare-event simulation, mediation pathway analysis, network analysis, statistical machine learning, and also applications in statistical genetics and genomics and metabolomics. She received her Ph.D. in Statistics from the University of Michigan advised by Prof. Gongjun Xu and Prof. Xuming He. Prior to Michigan, she received her B.S. in Statistics from the University of Science and Technology of China in 2016.

Making Sense of High Dimensional Data