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Ninth International Conference on Sensitivity Analysis of Model Output

  • Fechas:

    Del 28/10/19 al 30/10/19

  • Lugar:

    Universitat Oberta de Catalunya, Edifici B3, Parc Mediterrani de la Tecnologia, Avinguda Carl Friedrich Gauss, 5, 08860 Casteldefels, Barcelona, Castelldefels, Bajo Llobregat, España (mapa)

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Paula Rego, Self portrait in red (1962), detail, MNAC, Barcelona

CALL FOR PAPERS for the Ninth International Conference on Sensitivity Analysis of Model Output

Barcelona, October Monday 28 - Wednesday 30, 2019

"Are the results from a particular model more sensitive to changes in the model and the methods used to estimate its parameters, or to changes in the data?"

This remark by Giandomenico Majone goes the heart of the problem setting of sensitivity analysis, a tool which all modellers from all fields of application use to improve the quality of their inference.  Sensitivity Analysis is crucial both in the model construction and model interpretation phases, and is considered an important ingredient of model verification and validation.

SAMO conferences are devoted to advances in research on sensitivity analysis methods and their interdisciplinary applications, they are held every third year. The aim of the SAMO conference in Barcelona is to bring together researchers involved in the development and improvement of methods and strategies and users of sensitivity analysis in all disciplines of science, including physics, operations research, chemistry, biology, nanotechnology, engineering, environmental science, nuclear and industrial safety, economics and finance, and many others.

Special issues: After the conference two special issues will be prepared, one on Reliability Engineering and System Safety, edited by Bertrand Iooss and Bruno Sudret,  and one on another journal to be selected. 


See previous SAMO conferences.

Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be apportioned to different sources of uncertainty in its inputs. A related practice is uncertainty analysis, which has a greater focus on uncertainty quantification and propagation of uncertainty; ideally, uncertainty and sensitivity analysis should be run in tandem (Source: https://en.wikipedia.org/wiki/Sensitivity_analysis)

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Keynote speakers

Emanuele BorgonovoDepartment of Decision Sciences, Bocconi University, Milan, Italy.

Emanuele Borgonovo is Full Professor at the Department of Decision Sciences of Bocconi University, and director of the new Bachelor in Economics, Management and Computer Science. He is a fellow of Bocconi Institute for Data Science and Analytics. He is the co-chair of the Uncertainty Analysis Committee of ESRA and has been recently nominated president elect of the Decision Analysis Society of INFORMS. He is co-editor in chief of the European Journal of Operational Research. He has worked in international research projects with institutions such as the Idaho National Laboratory, DOE, DARPA, CRA, the US Nuclear Regulatory Commission, MIT, and has won several national and international awards. His research interests concern Sensitivity Analysis, Decision Analysis, Risk Analysis and Uncertainty Quantification. In his works, he has introduced several new sensitivity analysis techniques. He is author of the book: “Sensitivity Analysis: An Introduction for the Management Scientist”.

     Paul ConstantineUniversity of Colorado, Boulder, United States.

Paul Constantine is an assistant professor in the Department of Computer Science at University of Colorado Boulder. He received a PhD from Stanford's Institute for Computational and Mathematical Engineering and was awarded the John von Neumann Postdoctoral Fellowship at Sandia National Labs. His interdisciplinary research interests include parameter reduction and uncertainty quantification for computational science and engineering models. For more info, visit www.cs.colorado.edu/~paco3637

David Higdon, Social Decision Analytics Laboratory, Biocomplexity Institute of Virginia Tech, United States.

Dave Higdon began his academic career at Duke University as part of the Statistical Science Department.  He then moved on to spent 14 years with the Statistical Sciences Group at Los Alamos National Laboratory, serving as Group leader for five years.  He is now a professor in the Social Decision Analytics Laboratory at Virginia Tech.  Dave has spent much of his career developing Bayesian approaches for combining physical observations with large-scale computational models for prediction and inference.  While much of Dave’s past experience focused on the analysis of physical systems, he has recently broadened his focus to include social systems as well.

Amandine Marrel, French Alternative Energies and Atomic Energy Commision, Cadarache, France.

After an engineering degree and a Master2 in applied mathematics from INSA Toulouse, Amandine Marrel defended her PhD (2008) in statistics at INSA, within a research contract with French Alternative Energies and Atomic Energy Commission (CEA). Her work deals with the subject of Gaussian process metamodel for sensitivity analysis of numerical models, with an application to a hydrogeological transport model. From 2008 to 2011, she worked as research engineer at IFPEN in the Reservoir Engineering Division, on the uncertainty management in numerical simulation, mainly motivated by oil exploration problems. Since 2011, she has been working at CEA of Cadarache in the Nuclear Energy Division, still as research scientist, for the development of probabilistic and statistical approaches for the uncertainty quantification, design, metamodeling and sensitivity analysis of computer experiments, in support of safety studies for nuclear reactors. In 2017, she obtained her habilitation thesis in Statistics at Toulouse University.

Giray Ökten, Florida State University, Tallahassee, United States.

Giray Ökten is a Professor of Mathematics in the Department of Mathematics, Florida State University. His research interests are in the theory of Monte Carlo and quasi-Monte Carlo methods, and their applications. He was awarded a Fulbright U.S. Scholar Award in 2015.

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