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- Danny C. Sorensen

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Mathematics
D-index
50
Citations
21,953
130
World Ranking
764
National Ranking
382

Engineering and Technology
D-index
52
Citations
22,077
136
World Ranking
1761
National Ranking
695

2010 - SIAM Fellow For contributions to numerical linear algebra, optimization, and model reduction.

2009 - Fellow of the American Statistical Association (ASA)

- Eigenvalues and eigenvectors
- Algorithm
- Algebra

Danny C. Sorensen mostly deals with Eigenvalues and eigenvectors, Mathematical optimization, Applied mathematics, Singular value decomposition and Algorithm. Danny C. Sorensen works in the field of Eigenvalues and eigenvectors, namely Arnoldi iteration. Danny C. Sorensen has included themes like Newton's method and Trust region in his Mathematical optimization study.

His research in Applied mathematics intersects with topics in Jacobi eigenvalue algorithm and Algebra. His work in Singular value decomposition addresses subjects such as Scale, which are connected to disciplines such as Dynamical systems theory and Reduction methods. His studies deal with areas such as Stability, Matrix and Numerical stability as well as Algorithm.

- ARPACK Users' Guide: Solution of Large-Scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods (2399 citations)
- Computing a Trust Region Step (1100 citations)
- Nonlinear Model Reduction via Discrete Empirical Interpolation (1035 citations)

Danny C. Sorensen focuses on Eigenvalues and eigenvectors, Applied mathematics, Mathematical optimization, Mathematical analysis and Algorithm. His Eigenvalues and eigenvectors research is multidisciplinary, incorporating perspectives in Matrix, Software, Numerical analysis and Linear algebra. His research investigates the link between Matrix and topics such as Factorization that cross with problems in Parallel computing.

His biological study spans a wide range of topics, including Iterative method, Linear system, Generalized minimal residual method, Arnoldi iteration and Lanczos algorithm. His Mathematical optimization study combines topics from a wide range of disciplines, such as Singular value decomposition, Reduction, Hessian matrix and Trust region. His work is dedicated to discovering how Mathematical analysis, Nonlinear system are connected with Interpolation, Partial differential equation, Projection and Domain decomposition methods and other disciplines.

- Eigenvalues and eigenvectors (23.68%)
- Applied mathematics (21.05%)
- Mathematical optimization (21.05%)

- Nonlinear system (9.87%)
- Mathematical analysis (16.45%)
- Mathematical optimization (21.05%)

His primary areas of investigation include Nonlinear system, Mathematical analysis, Mathematical optimization, Applied mathematics and Reduction. His Nonlinear system study integrates concerns from other disciplines, such as Projection, Domain decomposition methods, Partial differential equation, Interpolation and Discretization. His work deals with themes such as Dynamical systems theory and Eigenvalues and eigenvectors, which intersect with Mathematical analysis.

The various areas that he examines in his Mathematical optimization study include Shape optimization, Hessian matrix and Trust region. His Applied mathematics research is multidisciplinary, incorporating elements of LTI system theory, Jacobian matrix and determinant, Generalized minimal residual method, Numerical analysis and Solver. While the research belongs to areas of Factorization, Danny C. Sorensen spends his time largely on the problem of Matrix, intersecting his research to questions surrounding Singular value decomposition.

- Nonlinear Model Reduction via Discrete Empirical Interpolation (1035 citations)
- The ground state correlation energy of the random phase approximation from a ring coupled cluster doubles approach. (213 citations)
- Discrete Empirical Interpolation for nonlinear model reduction (127 citations)

- Algorithm
- Eigenvalues and eigenvectors
- Mathematical analysis

His main research concerns Mathematical analysis, Nonlinear system, Projection, Interpolation and Mathematical optimization. His work on Dynamical systems theory expands to the thematically related Mathematical analysis. The Projection study combines topics in areas such as Finite difference, Galerkin method and Applied mathematics.

His Interpolation study which covers Dimension that intersects with Dimensionality reduction, State variable and Reduction. His work in Mathematical optimization covers topics such as Shape optimization which are related to areas like Continuous optimization. His Numerical analysis research includes elements of Truncation and Differential algebraic equation.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

ARPACK Users' Guide: Solution of Large-Scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods

R. B. Lehoucq;D. C. Sorensen;C. Yang.

**(1998)**

3782 Citations

Computing a Trust Region Step

Jorge J. Moré;D. C. Sorensen.

Siam Journal on Scientific and Statistical Computing **(1983)**

1841 Citations

Nonlinear Model Reduction via Discrete Empirical Interpolation

Saifon Chaturantabut;Danny C. Sorensen.

SIAM Journal on Scientific Computing **(2010)**

1595 Citations

Implicit application of polynomial filters in a k-step Arnoldi method

D. C. Sorensen.

SIAM Journal on Matrix Analysis and Applications **(1992)**

1496 Citations

Deflation Techniques for an Implicitly Restarted Arnoldi Iteration

R. B. Lehoucq;D. C. Sorensen.

SIAM Journal on Matrix Analysis and Applications **(1996)**

864 Citations

A Survey of Model Reduction Methods for Large-Scale Systems

A.C. Antoulas;D.C. Sorensen;S. Gugercin.

**(2000)**

857 Citations

Solving Linear Systems on Vector and: Shared Memory Computers

Jack J. Dongarra;Iain S. Duff;Danny C. Sorensen;Henk Van Der Vorst.

**(1990)**

815 Citations

Numerical linear algebra for high-performance computers

Jack J. Dongarra;Lain S. Duff;Danny C. Sorensen;Henk A. Vander Vorst.

**(1998)**

783 Citations

Newton's method with a model trust region modification

D. C. Sorensen.

SIAM Journal on Numerical Analysis **(1982)**

765 Citations

LAPACK: a portable linear algebra library for high-performance computers

E. Anderson;Z. Bai;J. Dongarra;A. Greenbaum.

conference on high performance computing (supercomputing) **(1990)**

661 Citations

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