Chunming Zhang is a Chinese and American statistician whose research involves nonparametric statistics and semiparametric models with applications including neuroscience and statistical finance. She is a professor of statistics at the University of Wisconsin–Madison,^[1] and the chair of the Nonparametric Statistics Section of the American Statistical Association.^[2]

Zhang was an undergraduate at Nankai University, and earned a master's degree through the Chinese Academy of Sciences.^[3] She completed a Ph.D. at the University of North Carolina at Chapel Hill in 2000. Her dissertation, Topics in the Generalized Likelihood Ratio Test, was supervised by Jianqing Fan.^[4]

She joined the University of Wisconsin–Madison as an assistant professor in 2000, and has been a full professor since 2010.^[3]

Zhang was elected as a Fellow of the Institute of Mathematical Statistics in 2011, "for influential contributions to theory and methodology for high-dimensional data, for unifying common loss functions through Bregman divergence, and for fundamental work in nonparametric and semiparametric methodology together with applications in multiple testing, brain-imaging and finance".^[5]

She became a Fellow of the American Statistical Association in 2016.^[6] She is a 2024 Medallion Lecturer of the Institute of Mathematical Statistics.^[7]

• Chunming Zhang publications indexed by Google Scholar