List of Joint Publications

Books:
Model Reduction and Approximation: Theory and Algorithms.
P. Benner, M. Ohlberger, A. Cohen, and K. Willcox, eds.
Philadelphia, PA: Society for Industrial and Applied Mathematics, 2017.
[ISBN: 978-1-611974-81-2].
DOI: 10.1137/1.9781611974829.

Model Reduction of Parametrized Systems.
P. Benner, M. Ohlberger, A. T. Patera, G. Rozza, and K. Urban, eds.
Springer International Publishing, 2017.
[ISBN: 978-3-319-58786-8].
DOI: 10.1007/978-3-319-58786-8.

Passive Macromodeling: Theory and Applications.
S. Grivet-Talocia and B. Gustavsen, eds.
John Wiley and Sons, 2016.
[ISBN: 978-1-119-14093-1].
DOI: 10.1002/9781119140931.

Book Chapters:
Model Order Reduction Based on System Balancing.
Peter Benner and Tobias Breiten.
In: Model Reduction and Approximation. Ed. by P. Benner, A. Cohen, M. Ohlberger, and K. Willcox.
Computational Science & Engineering. Philadelphia, PA: SIAM, 2017, pp. 261-295.
[ISBN: 978-1-611974-81-2].

Accelerating Band Linear Algebra Operations on GPUs with Application in Model Reduction.
Peter Benner, Ernesto Dufrechou, Pablo Ezzatti, Pablo Igounet, Enrique S. Quintana-Ortí, and Alfredo Remón.
In: Computational Science and Its Applications – ICCSA 2014: 14th International Conference, Guimarães, Portugal, June 30-July 3, 2014, Proceedings, Part VI. Ed. by B. Murgante, S. Misra, A. M. A. C. Rocha, C. Torre, J. G. Rocha, M. I. Falcão, D. Taniar, B. O. Apduhan, and O. Gervasi. Vol. 8584.
Lecture Notes in Comput. Sci. Cham: Springer, 2014, pp. 386-400.
[ISBN: 978-331909152-5].
DOI: 10.1007/978-3-319-09153-2_29.

Reduced-Order Multiobjective Optimal Control of Semilinear Parabolic Problems.
Laura Iapichino, Stefan Trenz, and Stefan Volkwein.
In: Numerical Mathematics and Advanced Applications ENUMATH 2015. Ed. by B. Karasözen, M. Manguoglu, M. Tezer-Sezgin, S. Göktepe, and Ö. Ugur.
Lect. Notes Comput. Sci. Eng. European Conference on Numerical Mathematics and Advanced Applications (ENUMATH), Middle E Tech Univ, Inst Appl Math, Ankara, TURKEY, SEP 14-18, 2015.
Cham: Springer International Publishing, 2016, pp. 389-397.
[ISBN: 978-3-319-39929-4].
DOI: 10.1007/978-3-319-39929-4_37.

Model Order Reduction for Pattern Formation in FitzHugh-Nagumo Equations.
Bülent Karasözen, Murat Uzunca, and Tugba Küçükseyhan.
In: Numerical Mathematics and Advanced Applications ENUMATH 2015. Ed. by B. Karasözen, M. Manguoglu, M. Tezer-Sezgin, S. Göktepe, and Ö. Ugur.
Lect. Notes Comput. Sci. Eng. European Conference on NumericalMathematics and Advanced Applications (ENUMATH), Middle E Tech Univ, Inst Appl Math, Ankara, TURKEY, SEP 14-18, 2015.
Cham: Springer International Publishing, 2016, pp. 369-377.
[ISBN: 978-3-319-39929-4].
DOI: 10.1007/978-3-319-39929-4_35.

Energy stable model order reduction for the Allen-Cahn equation.
Murat Uzunca and Bulent Karasözen.
In: Model Reduction of Parametrized Systems III. Ed. by F. Ferrari, P. Benner, G. Rozza, A. Patera, A. Vanegas, K. Urban, and M. Ohlberger.
to appear. Berlin-Heidelberg: Springer, 2017. Chap. 25, pp. -.

Articles:
Model Order Reduction of an Electro-Thermal Package Model.
N. Banagaaya, L. Feng, P. Meuris, W. Schoenmaker, and P. Benner.
In: IFAC-PapersOnLine 48 (2015), pp. 934-935.
DOI: 10.1016/j.ifacol.2015.05.212.

Two-Sided Projection Methods for Nonlinear Model Order Reduction.
P. Benner and T. Breiten.
In: SIAM J. Sci. Comput. 37.2 (2015), B239-B260.
DOI: 10.1137/14097255X.

Extending Lyapack for the Solution of Band Lyapunov Equations on Hybrid CPU-GPU Platforms.
P. Benner, A. Remón, E. Dufrechou, P. Ezzatti, and E. S. Quintana-Ortí.
In: J. Supercomput. 71.2 (Feb. 2015), pp. 740-750.
DOI: 10.1007/s11227-014-1322-7.

Semi-Active Damping Optimization of Vibrational Systems using the Parametric Dominant Pole Algorithm.
P. Benner, P. Kürschner, Z. Tomljanović, and N. Truhar.
In: Z. Angew. Math. Mech. 96.5 (2016), pp. 604-619.
DOI: 10.1002/zamm.201400158.

Unleashing GPU Acceleration for Symmetric Band Linear Algebra Kernels and Model Reduction.
P. Benner, E. Dufrechou, P. Ezzatti, E. S. Quintana-Ortí, and A. Remón.
In: Cluster Comp. 18.4 (Dec. 2015), pp. 1351-1362.
DOI: 10.1007/s10586-015-0489-x.

Reduced basis methods for pricing options with the Black-Scholes and Heston model.
O. Burkovska, B. Haasdonk, J. Salomon, and B. Wohlmuth.
In: SIAM J. Financ. Math. 6.1 (2015), pp. 685-712.
DOI: 10.1137/140981216.

Parallel Model Order Reduction of Sparse Electromagnetic/Circuit Models.
G. De Luca, G. Antonini, and P. Benner.
In: Appl. Comput. Electrom. 30.1 (Jan. 2015), pp. 1-21.
[ISSN: 1054-4887].

Fast and Accurate Time-Domain Simulations of Integer-N PLLs.
G. De Luca, P. Bolcato, R. Larcheveque, J. Rommes, and W. H. A. Schilders.
In: IEEE T. Circuits-I 64.4 (Apr. 2017), pp. 931–944.
[ISSN: 1549-8328].
DOI: 10.1109/TCSI.2016.2628323.

Simple hierarchical models of the Transcranial Magnetic Stimulation
Daniel Ioan, Ruxandra Barbulescu, Jean Ciurea, Gabriela Ciuprina, Przemyslaw Syrek
THE 10th INTERNATIONAL SYMPOSIUM ON ADVANCED TOPICS IN ELECTRICAL ENGINEERING March 23-25, 2017 Bucharest, Romania.

Parametric Modeling and Model Order Reduction for (Electro-)Thermal Analysis of Nanoelectronic Structures
Lihong Feng, Yao Yue, Nicodemus Banagaaya, Peter Meuris, Wim Schoenmaker, and Peter Benner
Journal of Mathematics in Industry, Vol. 6, Art. 10 (16pp.), 2016.
DOI: 10.1186/s13362-016-0030-8.

Fast and Accurate Model Reduction for Spectral Methods in Uncertainty Quantification.
F. D. Freitas, R. Pulch, and J. Rommes.
In: Int. J. for Uncertainty Quantification 6.3 (2016), pp. 271–286.
[ISSN: 2152-5080].
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016646.

To Be or Not to be Intrusive? The Solution of Parametric and Stochastic Equations—Proper Generalized Decomposition.
L. Giraldi, D. Liu, H. G. Matthies, and A. Nouy.
In: SIAM J. Sci. Comput. 37.1 (2015), A347– A368.
DOI: 10.1137/140969063.

To Be or Not to Be Intrusive? The Solution of Parametric and Stochastic Equations—the “Plain Vanilla” Galerkin Case.
L. Giraldi, A. Litvinenko, D. Liu, H. G. Matthies, and A. Nouy.
In: SIAM J. Sci. Comput. 36.6 (2014), A2720–A2744.
DOI: 10.1137/130942802.

Black-box macromodeling and its EMC applications.
S. Grivet-Talocia and B. Gustavsen.
In: IEEE Electroman. Comp. M. 5.3 (2016), pp. 71– 78.
[ISSN: 2162-2264].
DOI: 10.1109/MEMC.0.7764255.

Thermal Noise Compliant Synthesis of Linear Lumped Macromodels.
S. Grivet-Talocia, G. Signorini, S. B. Olivadese, C. Siviero, and P. Brenner.
In: IEEE Trans. Compon. Packag. Manuf. Technol. 5.1 (Jan. 2015), pp. 75–85.
[ISSN: 2156-3950].
DOI: 10.1109/TCPMT.2014.2370096.

Multiobjective PDE-constrained Optimization using the Reduced-Basis Method.
L. Iapichino, S. Ulbrich, and S. Volkwein.
In: Adv. Comput. Math. (Jan. 2017).
[ISSN: 1572-9044].
DOI: 10.1007/s10444-016-9512-x.

An Inverse Iteration Method for Eigenvalue Problems with Eigenvector Nonlinearities.
E. Jarlebring, S. Kvaal, and W. Michiels.
In: SIAM J. Sci. Comput. 36.4 (2014), A1978–A2001.
DOI: 10.1137/130910014.

Model Order Reduction for Nonlinear Schrödinger Equation.
B. Karasözen, C. Akkoyunlu, and M. Uzunca.
In: Appl. Math. Comput. 258 (May 2015), pp. 509–519.
[ISSN: 0096-3003].
DOI: 10.1016/j.amc.2015.02.001.

Structure preserving integration and model order reduction of skew-gradient reaction–diffusion systems.
B. Karasözen, T. Küçükseyhan, and M. Uzunca.
In: Ann. Oper. Res. (Nov. 2015), pp. 1–28.
[ISSN: 1572-9338].
DOI: 10.1007/s10479-015-2063-6.

The Localized Reduced Basis Multiscale Method for Two-Phase Flows in Porous Media.
S. Kaulmann, B. Flemisch, B. Haasdonk, K.-A. Lie, and M. Ohlberger.
In: Internat. J. Numer. Methods Engrg. 102.5 (2015), pp. 1018–1040.
DOI: 10.1002/nme.4773.

Krylov Approximation of Linear ODEs with Polynomial Parameterization.
A. Koskela, E. Jarlebring, and M. E. Hochstenbach.
In: SIAM J. Matrix Anal. Appl. 37.2 (2016), pp. 519–538.
DOI: 10.1137/15M1032831.

Certified Reduced Basis Approximation for the Coupling of Viscous and Inviscid Parametrized Flow Models.
I. Martini, G. Rozza, and B. Haasdonk.
In: SIAM J. Sci. Comput. (2017).
DOI: 10.1007/s10915-017- 0430-y.

Reduced basis approximation and a-posteriori error estimation for the coupled Stokes-Darcy system.
I. Martini, G. Rozza, and B. Haasdonk.
In: Adv. Comput. Math. 41.5 (2015), pp. 1131–1157.
DOI: 10.1007/s10444- 014-9396-6.

Analysis of an Iteration Method for the Algebraic Riccati Equation.
A. Massoudi, M. R. Opmeer, and T. Reis.
In: SIAM J. Matrix Anal. Appl. 37.2 (2016), pp. 624–648.
DOI: 10.1137/140985792.

The ADI method for bounded real and positive real Lur’e equations.
A. Massoudi, M. R. Opmeer, and T. Reis.
In: Numer. Math. 135.2 (Feb. 2017), pp. 431–458.
[ISSN: 0945-3245].
DOI: 10.1007/s00211-016-0805-2.

Macromodel- Based Iterative Solvers for Simulation of High-Speed Links With Nonlinear Terminations.
S. B. Olivadese, S. Grivet-Talocia, C. Siviero, and D. Kaller.
In: IEEE Trans. Compon. Packag. Manuf. Technol. 4.11 (Nov. 2014), pp. 1847–1861.
[ISSN: 2156-3950].
DOI: 10.1109/TCPMT.2014.2359982.

Parameterized and DC-Compliant Small-Signal Macromodels of RF Circuit Blocks.
S. B. Olivadese, G. Signorini, S. Grivet-Talocia, and P. Brenner.
In: IEEE Trans. Compon. Packag. Manuf. Technol. 5.4 (Apr. 2015), pp. 508–522.
[ISSN: 2156-3950].
DOI: 10.1109/TCPMT.2015.2403071.

A Lower Bound for the Balanced Truncation Error for MIMO Systems.
M. R. Opmeer and T. Reis.
In: IEEE Trans. Autom. Control 60.8 (Aug. 2015), pp. 2207–2212.
[ISSN: 0018-9286].
DOI: 10.1109/TAC.2014.2368232.

Stochastic Galerkin Methods and Model Order Reduction for Linear Dynamical Systems.
R. Pulch and E. Jan W. ter Maten.
In: Int. J. for Uncertainty Quantification 5.3 (2015), pp. 255–273.
[ISSN: 2152-5080].
DOI: 10.1615/Int.J.UncertaintyQuantification.2015010171.

Sensitivity analysis and model order reduction for random linear dynamical systems.
R. Pulch, E. Jan W. ter Maten, and F. Augustin.
In: Math. Comput. Simulat. 111 (2015), pp. 80–95.
[ISSN: 0378-4754].
DOI: 10.1016/j.matcom.2015.01.003.

Macromodeling of I/O Buffers via Compressed Tensor Representations and Rational Approximations.
G. Signorini, C. Siviero, S. Grivet-Talocia, and I. S. Stievano.
In: IEEE Trans. Compon. Packag. Manuf. Technol. 6.10 (Oct. 2016), pp. 1522–1534.
[ISSN: 2156-3950].
DOI: 10.1109/TCPMT.2016.2602212.

Preprints:
A. Alla, M. Falcone, and S. Volkwein.
Error analysis for POD approximations of infinite horizon problems via the dynamic programming approach.
Konstanzer Schriften in Mathematik. Sept. 2015.
http://nbn-resolving.de/urn:nbn:de:bsz:352-0-300231

C. Beattie, V. Mehrmann, H. Xu, and H. Zwart.
Port-Hamiltonian Descriptor Systems.
arXiv e-prints 1705.09081. math.OC. Cornell University, May 2017.
https://arxiv.org/abs/1705.09081

A. Falcó, W. Hackbusch, and A. Nouy.
On the Dirac-Frenkel variational principle on tensor Banach spaces.
arXiv e-prints 1610.09865. math.NA. Cornell University, Oct. 2016.
https://arxiv.org/abs/1610.09865

Conference Papers:
Model Order Reduction for Nanoelectronics Coupled Problems with Many Inputs.
N. Banagaaya, L. Feng, W. Schoenmaker, P. Meuris, A. Wieers, R. Gillon, and P. Benner.
In: Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition. 2016, pp. 313– 318.
[ISBN: 978-3-9815-3707-9].

Parametrized reduced model of RF MEMS ca- pacitive switch.
S. Kula and A. S. Lup.
In: 2017 10th International Symposium on Advanced Topics in Electrical Engineering (ATEE). Mar. 2017, pp. 529–532.
DOI: 10.1109/ATEE.2017.7905180.

Loewner-based macromodeling with exact interpolation constraints.
S. Lefteriu and S. Grivet-Talocia.
In: 2016 IEEE 25th Conference on Electrical Performance Of Electronic Packaging And Systems (EPEPS). Oct. 2016, pp. 43–46.
DOI: 10.1109/EPEPS.2016.7835414.

Families of moment matching-based reduced order models for linear descriptor systems.
P. Schulze, T. C. Ionescu, and J. M. A. Scherpen.
In: European Control Conference (ECC). 2016, pp. 1964–1969.
DOI: 10.1109/ ECC.2016.7810579.

Behavioral Macromodeling of High-Speed Drivers via Compressed Tensor Representations.
C. Siviero, S. Grivet-Talocia, I. S. Stievano, and G. Signorini.
In: 2015 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO). Invited paper. Aug. 2015, pp. 1–3.
DOI: 10.1109/NEMO.2015.7415004.

Application of Krylov-type Parametric Model Order Reduction in Efficient Uncertainty Quantification of Electro-thermal Circuit Models.
Y. Yue, L. Feng, P. Meuris, W. Schoenmaker, and P. Benner.
In: Proceedings of the Progress In Electromagnetics Research Symposium (PIERS 2015). 2015, pp. 379–384.
DOI: 10.17617/2.2223025.