معرفی
David Ruppert is the Andrew Schultz Jr. Professor of Engineering at Cornell University's School of Operations Research and Information Engineering, and Professor of Statistics and Data Science. He holds dual appointments and has been a faculty member since 1987. His education includes a B.A. in Mathematics from Cornell University (1970), M.A. in Mathematics from the University of Vermont (1973), and Ph.D. in Statistics and Probability from Michigan State University (1977).
Research Interests: His work spans functional data analysis, astrostatistics, neuroimaging (fMRI/ICA), environmental statistics, and semiparametric regression. He has pioneered methods in measurement error models, splines, and Bayesian statistics. His research has been continuously funded by NSF, NIH, and EPA since 1978.
Publications: Over 130 refereed articles and 5 books, including foundational texts like Measurement Error in Nonlinear Models and Statistics and Data Analysis for Financial Engineering. Recent work includes astrostatistical modeling of galaxy spectral energy distributions and neuroimaging analysis.
Awards/Honors: Wilcoxon Prize (1986), ASA/IMS Fellowships, Highly Cited Researcher (ISI), and Distinguished Alumni Award (2014).
Teaching: Courses include Financial Engineering, Bayesian Statistics, and Functional Data Analysis. He co-developed four graduate/undergraduate courses at Cornell.
Service: Editor of Journal of the American Statistical Association, Director of the MPS Program in Data Science and Statistics (DSS).
Impact: 29 PhD students trained, many now leading researchers in academia and industry.
