Diaz De La O, Francisco Alejandro - University of Liverpool

个人简介

I am an applied mathematician working on computational Bayesian methods, model calibration and metamodelling. My priority is to establish links with industry to develop fundamental methods and promote the use of uncertainty quantification techniques. To this effect, I am part of the steering committee of the Special Interest Group on Uncertainty Quantification and Management in High Value Manufacturing, established by the Knowledge Transfer Network. In this capacity, I have organised a study group with industry where 50 academics, PDRAs and doctoral students worked through challenges to help promote good industrial practice on uncertainty quantification (http://studygroup.riskinstitute.org.uk/). I am the programme director of the MRes and MSc in Risk and Uncertainty within the Institute for Risk and Uncertainty. I am a member of the Committee on Probability and Statistics in the Physical Sciences at the Bernoulli Society for Mathematical Statistics and Probability. I am also a member of the EPSRC Mathematical Sciences Early Career Forum. Programme Director for the MRes and MSc in Decision Making under Risk and Uncertainty PhD Research Officer Maths Coordinator

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Bayesian updating and model class selection with Subset Simulation Gaussian process hyper-parameter estimation using Parallel Asymptotically Independent Markov Sampling TRANSITIONAL ANNEALED ADAPTIVE SLICE SAMPLING FOR GAUSSIAN PROCESS HYPER-PARAMETER ESTIMATION Uncertainty quantification in DIC with Kriging regression Analysis of cross-laminated timber by computational homogenisation and experimental validation Full-field digital image correlation with Kriging regression. The use of Kriging in stochastic model updating and its effect on parameter estimates A hybrid spectral and metamodeling approach for the stochastic finite element analysis of structural dynamic systems Approximate bayesian computation for finite element model updating Conceptual Comparison of Bayesian Approaches and Imprecise Probabilities. Inferring structural variability using modal analysis in a Bayesian framework Investigation on the extensibility of the wood cell-wall composite by an approach based on homogenisation and uncertainty analysis Mathematical modelling of the stochastic mechanical properties of wood and its extensibility at small scales Optimal sensor placement in timber structures by means of a multi-scale approach with material uncertainty Probabilistic Sensitivity Analysis of Corrugated Skins with Random Elastic Parameters and Surface Topology Span Morphing Using the Compliant Spar Stochastic structural dynamic analysis using Bayesian emulators A computational approach for the random mechanical response of foam-filled honeycomb cores A computational multi-scale approach for the stochastic mechanical response of foam-filled honeycomb cores Bayesian assimilation of multi-fidelity finite element models Bayesian assimilation of multi-fidelity stochastic finite element models Gaussian process emulators for the stochastic finite element method. Structural dynamic analysis using Gaussian process emulators Coupling polynomial chaos expansions with Gaussian process emulators: An introduction Gaussian process emulators for dynamical systems with random parameters