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Marc G. Genton

Distinguished Professor, Statistics

Computer, Electrical and Mathematical Science and Engineering Division


Spatio-Temporal Statistics & Data Science

Affiliations

Education Profile

  • ​​​​Ph.D., Statistics, Swiss Federal Institute of Technology (EPFL), Lausanne, 1996
  • M.Sc., Applied Mathematics Teaching, Swiss Federal Institute of Technology (EPFL), Lausanne, 1994
  • B.Sc., Engineer in Applied Mathematics, Swiss Federal Institute of Technology (EPFL), Lausanne, 1992

Research Interests

​Professor Genton's main research interests concern statistical analysis, visualization, modeling, prediction, and uncertainty quantification of spatio-temporal data, with applications in environmental and climate science, renewable energies such as wind and solar power, geophysics, and marine science. His research activities also include skewed multivariate non-Gaussian distributions and robust statistics.

Selected Publications

  • ​Genton, M. G., Keyes, D., and Turkiyyah, G. (2018), "Hierarchical decompositions for the computation of high-dimensional multivariate normal probabilities," Journal of Computational and Graphical Statistics, in press.
  • Jeong, J., Jun, M. and Genton, M. G. (2017), "Spherical process models for global spatial statistics," Statistical Science, 32, 301-513.
  • Xu, G., and Genton, M. G. (2017) "Tukey g-and-h random fields," Journal of the American Statistical Association, 112, 1236-1249.
  • Genton, M. G. and Hall, P. (2016), "A tilting approach to ranking influence," Journal of the Royal Statistical Society Series B, 78, 77-97.
  • Sun, Y., and Genton, M. G. (2011), "Functional boxplots," Journal of Computational and Graphical Statistics, 20, 316-334.