About the Conference

Description

Computational Science and Engineering (CS&E) is now widely accepted, along with theory and experiment, as a crucial third mode of scientific investigation and engineering design. Aerospace, automotive, biological, chemical, semiconductor, and other industrial sectors now rely on simulation for technical decision support. For government agencies also, CS&E has become an essential support for decisions on resources, transportation, and defense. Finally, in many new areas such as medicine, the life sciences, management and marketing (e.g. data- and stream mining), and finance techniques and algorithms from CS&E are of growing importance.

CS&E is by nature interdisciplinary. It grows out of physical applications and it depends on computer architecture, but at its heart are powerful algorithms. Much of CS&E has involved analysis, but the future surely includes optimization and design, especially in the presence of uncertainty. Another mathematical frontier is the assimilation of very large data sets through such techniques as adaptive multiresolution, automated feature search, and low-dimensional parameterization.

SIAM is conducting this conference on CS&E to draw attention to the tremendous range of major computational efforts on large problems in science and engineering, to promote the interdisciplinary culture required to meet these large-scale challenges, and to encourage the training of the next generation of computational scientists.

Funding Agency

SIAM and the conference Organizing Committee wish to extend their thanks and appreciation to the National Science Foundation for its support of this conference.

Themes

Advanced Discretization Methods
Analysis Validation and Verification
Computational Biology and Bioinformatics
Computational Chemistry and Chemical Engineering
Computational Dynamical Systems
Computational Earth and Atmospheric Sciences
Computational Electromagnetics
Computational Finance
Computational Fluid Dynamics
Computational Medicine and Bioengineering
Computational Nanoscience
Computational Physics and Astrophysics
Computational Solid Mechanics and Materials
CS&E Education
Data-Centric Computing
Discrete and Combinatorial Algorithms for CS&E
High Dimensional Applications
High Productivity Computing
Imaging and Graphics
Inverse Problems
Meshing and Adaptivity
Multiscale and Multiphysics Problems
Numerical Algorithms for CS&E
Optimal Design, Optimal Control, and Inverse Problems
Parallel and Distributed Computing
Problem-Solving Environments
Semiconductor Device Simulation
Software and Middleware Systems
Stochastic Partial Differential Equations and Applications
Uncertainty Estimation and Sensitivity
Visualization and Human-Computer Interaction

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