What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Statistics
- Mathematical analysis
Applied mathematics, Uncertainty quantification, Mathematical analysis, Random element and Random field are his primary areas of study.
His studies in Applied mathematics integrate themes in fields like Stochastic modelling, Random matrix, Stochastic process, Mathematical optimization and Calculus.
His Uncertainty quantification research incorporates themes from Nonparametric statistics, Dynamical systems theory, Probabilistic logic, Statistical physics and Computational mechanics.
Christian Soize interconnects Monte Carlo method and Dissipative system in the investigation of issues within Mathematical analysis.
His work deals with themes such as Stochastic simulation, Probability distribution, Random function and Multivariate random variable, which intersect with Random element.
His work in Random field tackles topics such as Polynomial chaos which are related to areas like Inverse problem and Random variable.
His most cited work include:
- Physical Systems with Random Uncertainties: Chaos Representations with Arbitrary Probability Measure (405 citations)
- A nonparametric model of random uncertainties for reduced matrix models in structural dynamics (355 citations)
- Maximum entropy approach for modeling random uncertainties in transient elastodynamics. (260 citations)
What are the main themes of his work throughout his whole career to date?
Christian Soize mainly focuses on Uncertainty quantification, Applied mathematics, Probabilistic logic, Mathematical analysis and Nonlinear system.
The various areas that he examines in his Uncertainty quantification study include Nonparametric statistics, Random matrix, Parametric statistics, Mathematical optimization and Statistical model.
The various areas that Christian Soize examines in his Applied mathematics study include Random variable, Multivariate random variable, Principle of maximum entropy, Stochastic process and Random field.
His Probabilistic logic research is multidisciplinary, relying on both Algorithm, Optimization problem, Computational model and Dynamical systems theory.
As part of one scientific family, Christian Soize deals mainly with the area of Mathematical analysis, narrowing it down to issues related to the Finite element method, and often Discretization.
His biological study spans a wide range of topics, including Vibration, Mistuning and Mechanics.
He most often published in these fields:
- Uncertainty quantification (28.62%)
- Applied mathematics (22.62%)
- Probabilistic logic (22.31%)
What were the highlights of his more recent work (between 2016-2021)?
- Probabilistic logic (22.31%)
- Uncertainty quantification (28.62%)
- Applied mathematics (22.62%)
In recent papers he was focusing on the following fields of study:
Christian Soize mainly investigates Probabilistic logic, Uncertainty quantification, Applied mathematics, Nonlinear system and Algorithm.
He interconnects Basis, Nonparametric statistics, Mathematical optimization, Computational model and Hyperparameter in the investigation of issues within Probabilistic logic.
His studies in Uncertainty quantification integrate themes in fields like Random matrix, Mathematical analysis, Control theory, Reduction and Statistical physics.
In his articles, he combines various disciplines, including Applied mathematics and Context.
His Nonlinear system research is multidisciplinary, incorporating perspectives in Mistuning, Vibration, Finite element method and Mechanics, Slosh dynamics.
His Algorithm research also works with subjects such as
- Stochastic modelling, which have a strong connection to Jitter, Stochastic process, Probability density function and Inverse problem,
- Random field most often made with reference to Gaussian.
Between 2016 and 2021, his most popular works were:
- Stochastic modeling and identification of a hyperelastic constitutive model for laminated composites (28 citations)
- A nonparametric probabilistic approach for quantifying uncertainties in low-dimensional and high-dimensional nonlinear models (19 citations)
- Data-driven kernel representations for sampling with an unknown block dependence structure under correlation constraints (13 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Statistics
- Mathematical analysis
Christian Soize spends much of his time researching Probabilistic logic, Mathematical optimization, Uncertainty quantification, Applied mathematics and Nonlinear system.
The concepts of his Probabilistic logic study are interwoven with issues in Probability distribution, Diffusion map, Small data, Optimization problem and Stiefel manifold.
His research integrates issues of Nonparametric statistics, Probability density function and Multivariate random variable in his study of Mathematical optimization.
His research in Uncertainty quantification intersects with topics in Reduction, Model order reduction, Algorithm, Hyperparameter and Gaussian.
His Applied mathematics study incorporates themes from Basis, Random variable, Principle of maximum entropy, Random field and Eigenvalues and eigenvectors.
Christian Soize has researched Nonlinear system in several fields, including Vibration, Frequency band, Finite element method and Dissipative system.
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