SIAM-UQ 2016 - SIAM Conference on Uncertainty Quantification

Uncertainty quantification is critical to achieving validated predictive computations in a wide range of scientific and engineering applications. The field relies on a broad range of mathematics and statistics foundations, with associated algorithmic and computational development. This conference will bring together mathematicians, statisticians, scientists, and engineers with an interest in development and implementation of uncertainty quantification methods. While applications of UQ in many fields will be represented at the conference, the focal application for UQ16 is Life science. Other major conference themes include the mathematical foundation of UQ and the connections between UQ and big data. The goal of the meeting is to provide a forum for the sharing of ideas, and to enhance communication among this diverse group of technical experts, thereby contributing to future advances in the field.
Funding Agencies
nsf
SIAM and the Conference Organizing Committee wish to extend their thanks and appreciation to the U.S. National Science Foundation for its support of this conference.
Themes
Main themes
Mathematical foundations of UQ
UQ in Life Science
UQ in Data Science
Topics
Big data
Data assimilation
Decision support
Design of experiments
Functional data analysis
High-dimensional approximations
Inverse problems
Learning theory
Model bias and calibration
Multiscale methods
Optimization and control under uncertainty
Rare events
Risk assessment
Sampling methods
Sensitivity analysis
Spatial temporal statistical analysis
Stochastic / random differential equations
Surrogate models
Uncertainty propagation
Verification and validation
Visualization of uncertainties