Department of Health Studies and the College
With the advancement of technology, it is now easier to get access to large data sets. Compared with traditional data sets, such data has dramatically different features. The number of variables is in the order of millions, but the number of observations is relatively small: the so-called “large p, small n” paradigm. Hongyuan Cao’s research is mainly focused on such high-dimensional statistical inference with an emphasis on large-scale, multiple testing. It has applications in such areas as genomics and image analysis.
Another area of her research involves post-market safety studies of drugs. She is also developing statistical methods for correlated observational data. This has applications in such areas as clinical diagnosis and psychiatry.
Cao’s many awards include the Distinguished Student Paper Award from the Eastern North American Region of the International Biometric Society in 2009. She received her PhD in statistics from the University of North Carolina at Chapel Hill and her BS in mathematics and applied mathematics (with honors) from Zhejiang University.
Cao joined the University of Chicago faculty in 2010.