What is he best known for?
The fields of study he is best known for:
- Mathematical analysis
- Partial differential equation
- Numerical analysis
Mathematical optimization, Finite volume method, Partial differential equation, Numerical analysis and Nonlinear system are his primary areas of study.
His work carried out in the field of Mathematical optimization brings together such families of science as Discretization, Dynamical systems theory, Conservation law and Model order reduction.
His research investigates the connection between Finite volume method and topics such as Hyperbolic partial differential equation that intersect with problems in Differential operator, Interpolation and Linear equation.
His Partial differential equation study combines topics from a wide range of disciplines, such as Grid and Applied mathematics.
In Numerical analysis, Mario Ohlberger works on issues like Finite element method, which are connected to Structure, Theoretical computer science and Computational science.
His work is dedicated to discovering how Nonlinear system, Mathematical analysis are connected with Basis, Lie group and Group and other disciplines.
His most cited work include:
- A generic grid interface for parallel and adaptive scientific computing. Part II: implementation and tests in DUNE (328 citations)
- REDUCED BASIS METHOD FOR FINITE VOLUME APPROXIMATIONS OF PARAMETRIZED LINEAR EVOLUTION EQUATIONS (285 citations)
- A generic grid interface for parallel and adaptive scientific computing. Part I: abstract framework (254 citations)
What are the main themes of his work throughout his whole career to date?
Mario Ohlberger focuses on Applied mathematics, Mathematical optimization, Basis, Reduction and Discretization.
His Applied mathematics study integrates concerns from other disciplines, such as Computation, Finite element method and Parameter reduction.
The study incorporates disciplines such as Grid and Nonlinear system in addition to Mathematical optimization.
The Basis study combines topics in areas such as Partial differential equation, Parameterized complexity and Interpolation.
When carried out as part of a general Reduction research project, his work on Model order reduction is frequently linked to work in Gramian matrix, therefore connecting diverse disciplines of study.
While the research belongs to areas of Discretization, he spends his time largely on the problem of Finite volume method, intersecting his research to questions surrounding Conservation law, Geometry, Hyperbolic partial differential equation and Convection–diffusion equation.
He most often published in these fields:
- Applied mathematics (34.55%)
- Mathematical optimization (29.70%)
- Basis (27.88%)
What were the highlights of his more recent work (between 2016-2021)?
- Basis (27.88%)
- Reduction (24.24%)
- Applied mathematics (34.55%)
In recent papers he was focusing on the following fields of study:
Mario Ohlberger mainly focuses on Basis, Reduction, Applied mathematics, Model order reduction and A priori and a posteriori.
His Basis research includes elements of Partial differential equation and Parameterized complexity.
The concepts of his Partial differential equation study are interwoven with issues in Interpolation, Domain and Nonlinear system.
His Applied mathematics research is multidisciplinary, incorporating perspectives in Hessian matrix, Parametric model order reduction and Finite element method.
His Nonlinear programming research is multidisciplinary, incorporating elements of Discretization and Grid.
Mathematical analysis and Finite volume method are commonly linked in his work.
Between 2016 and 2021, his most popular works were:
- Model Reduction and Approximation: Theory and Algorithms (122 citations)
- Model Reduction of Parametrized Systems (33 citations)
- A new Heterogeneous Multiscale Method for the Helmholtz equation with high contrast (22 citations)
In his most recent research, the most cited papers focused on:
- Mathematical analysis
- Partial differential equation
- Algorithm
Mario Ohlberger mostly deals with Applied mathematics, Reduction, Finite element method, Basis and Algorithm.
By researching both Applied mathematics and A priori and a posteriori, Mario Ohlberger produces research that crosses academic boundaries.
His research integrates issues of Partial differential equation and Interpolation in his study of Reduction.
Mario Ohlberger has included themes like Series and Nonlinear system in his Finite element method study.
Mario Ohlberger integrates Basis and Estimator in his research.
His research in Algorithm focuses on subjects like Domain decomposition methods, which are connected to Model order reduction.
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