1. Opening:
Overview on Computer Experiments

   Speaker: Professor Jeff Wu (ISyE,
Gatech)

2. Title: Multi-Layer
Designs for Computer Experiments

   Speaker: Professor Roshan J.
Vengazhiyil (ISyE, Gatech)

Abstract: Computer experiments play a major role in the modern era
of scientific and technological development. In designing computer experiments,
Latin hypercube designs (LHDs) are widely used. However, finding an optimal LHD
is computationally cumbersome. On the other hand, although many optimal designs
are well known for physical experiments, the redundancy of design points make
them undesirable for computer experiments. In this work, we present a new class
of space-filling designs developed by splitting two-level full or fractional
factorial designs into multiple layers. The method takes advantages of many
available results in designing physical experiments and therefore, the proposed
Multi-layer designs (MLDs) are easy to generate. Moreover, our numerical study
shows that MLDs can have better space-filling properties than optimal LHDs.

3. Title: Some
New Advances in Design and Modeling of Computer Experiments

Speaker: Professor Peter Z. G. Qian (Statistics, Wisconsin)

Abstract: Computer models are now becoming ubiquitous in nearly all
fields of sciences and engineering. Design and modeling are two key aspects of
computer experiments. In this talk, I will report some recent advances in both
aspects. Specific topics include a new approach for emulation of computer
models with qualitative and quantitative factors; sequential space-filling
designs; Sudoku based space-filling designs; and sliced Latin hypercube designs
for ensembles of computer models. 

4. Title: Analysis
of Computer Experiments with Functional Response

   Speaker: Professor Ying Hung  (Statistics, Rutgers)

Abstract: Most existing methods for analyzing computer experiments
with single outputs such as kriging cannot be easily applied to functional
outputs due to the computational problems caused by high-dimensionality of the
response. In this paper, we develop an efficient implementation of kriging for
analyzing functional responses. Our methodology uses a two-stage model building
procedure with Kronecker products and an improved EM algorithm for estimation.
The methodology is illustrated using a computer experiment conducted for
optimizing residual stresses in machined parts. This is a joint work with V.
Roshan Joseph and Shreyes N. Melkote.