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MA 797

Uncertainty Quantification for Physical and Biological Models

Course Topics

  • Motivating applications and prototypical models
  • Fundamental aspects of probability, random processes and statistics
  • Representation of random inputs
  • Parameter selection techniques
  • Frequentist and Bayesian model calibration
  • Uncertainty propagation in models
  • Stochastic spectral methods and sparse grid techniques
  • Prediction in the presence of model discrepancy
  • Surrogate models
  • Global sensitivity analysis

Grade: Projects (can be done in groups of up to 3 or 4 students): 100%

Office hours: By appointment

Contact info: Ralph C. Smith, SAS 4140, Department of Mathematics, NCSU, Raleigh, NC 27695-8205, phone: 919-515-7552, fax: 919-515-1636, email: