Ander Gray received an MSci in Physics from Queen’s University Belfast (2017). Since then, he has been a PhD student at the University of Liverpool and Culham Centre for Fusion Energy, studying Uncertainty Quantification. For his thesis work, Ander researches methods for efficiently propagating uncertainty in radiation transport simulations. He is also involved in developing methods and software for calibrating and propagating uncertainties through computational models, in the form of imprecise probabilities.
This minisymposium presents modern approaches to analyze a variety of mathematical systems in Julia, via set propagation techniques: dynamical systems, cyber-physical systems, probabilistic systems, and neural networks. To deploy those systems in the real world there is an increasing demand for safe and reliable models. The speakers represent a broad cross-section of work from different fields that build on set-based techniques and global optimization to address such challenges.