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Accelerating Industrial Productivity via Deterministic Computer Experiments & Stochastic Simulation

5th September 2011 to 9th September 2011

Organisers: Derek Bingham (Simon Fraser University), Angela Dean (The Ohio State University), Tom Santner (Ohio State University), Bruce Ankenman (Northwestern University), and Barry Nelson (Northwestern University)

Workshop Theme

The objective of this workshop is to bring researchers from the deterministic computer experiment and stochastic simulation experiment communities together to share advances and diverse approaches for efficient design and analysis of such experiments.

Some of the challenges that both the stochastic simulation and deterministic computer simulation communities face arise from inputs that can be qualitative, quantitative, or a mixture of these two types. These experiments may include large numbers of inputs, not only control variable inputs but also inputs that describe environmental variation. The input regions may be constrained rather than hyper rectangular. Their outputs can be univariate, multivariate, or functional. In the case of multivariate output, the objective can be constrained optimization, contour estimation, or determination of Pareto optima. The cross-fertilization of ideas and approaches of the two research fields offers a natural confluence to spur the development of new methodology.

The presentations and panel discussions will be organized in sessions around the following themes:

  • Applications of Computer and Stochastic Simulation Experiments
  • Design of Computer Experiments
  • Prediction Methodology
  • Stochastic Simulation Experiments
  • Input Uncertainty
  • Sensitivity Analysis
  • Calibration Experiments
University of Cambridge Research Councils UK
    Clay Mathematics Institute The Leverhulme Trust London Mathematical Society Microsoft Research NM Rothschild and Sons