David Ruppert

Andrew Schultz Jr. Professor of Engineering
Operations Research and Information Engineering (ORIE)

David Ruppert is Andrew Schultz Jr. Professor of Engineering, School of Operations Research and Information Engineering, and Professor of Statistical Science, Cornell University. He received a BA in Mathematics from Cornell University in 1970, an MA in Mathematics from the University of Vermont in 1973, and a PhD in Statistics and Probability from Michigan State University in 1977. He was Assistant and then Associate Professor of Statistics at the University of North Carolina, Chapel Hill, from 1977 to 1987. He is a Fellow of the ASA and IMS and received the Wilcoxon Prize in 1986. Professor Ruppert was named "Highly cited" researcher by ISIHighlyCited.com and was ranked 21st in mathematics by journal citations. He has had 25 PhD students, many of them now leading researchers. Professor Ruppert has worked on stochastic approximation, transformations and weighting in regression, and smoothing. His current research focuses on astrostatistics, measurement error models, splines, semiparametric regression, and environmental statistics. He has published over 100 articles in refereed journals and has published five books, Transformation and Weighting in Regression, Measurement Error in Nonlinear Models (first and second editions), Semiparametric Regression, Statistics and Finance: An Introduction, and Statistics and Data Analysis for Financial Engineering.

  • Ruppert, David. 2010. Statistics and Data Analysis for Financial Engineering. New York, NY:Springer.
  • Carroll, R., David Ruppert, L. Stefanski, C Crainicanu. 2006. Measurement Error in Nonlinear Models, A Modern Perspective, 2nd Edition. (2) : 488. Chapman and Hall/CRC.
  • Ruppert, David. 2004. Statistics and Finance: An Introduction. New York, NY: Springer.
  • Ruppert, David, D. Wand, R Carroll. 2003. Semiparametric Regression. (12) : 404.Cambridge University Press.
  • Ruppert, David, C. Shoemaker, Y. Wang, Y. Li, N Bliznyuk. 2012. "Uncertainty Analysis for Computationally Expensive Models with Multiple Outputs." Journal of Agricultural, Biological, and Environmental Statistics 17 (4): 623-640.