Our research on optimal experimental design is highlighted on KAUST discovery
1 min read
·
A fast computational method optimizes sensor measurement networks for noisy, sparsely observed environments.
About
Taking the guesswork out of experimental design
The capture of information about environments and processes is ubiquitous in modern society, from recording weather patterns to measuring traffic density and industrial process parameters. These measurements, when collated, provide data for predictive modelling and process optimization.
Read the full article on KAUST discovery
Related People
Related Researchers
Marco Scavino
- Visiting Scholar, Stochastic Numerics Research Group
Quan Long
- Research Scientist, Stochastic Numerics Research Group
