Proper orthogonal decomposition closure models for turbulent flows: a numerical comparison Z Wang, I Akhtar, J Borggaard, T Iliescu Computer Methods in Applied Mechanics and Engineering 237, 10-26, 2012 | 355 | 2012 |

Variational multiscale proper orthogonal decomposition: Navier‐stokes equations T Iliescu, Z Wang Numerical Methods for Partial Differential Equations 30 (2), 641-663, 2014 | 139 | 2014 |

Two-level discretizations of nonlinear closure models for proper orthogonal decomposition Z Wang, I Akhtar, J Borggaard, T Iliescu Journal of Computational Physics 230 (1), 126-146, 2011 | 128 | 2011 |

Approximate deconvolution large eddy simulation of a barotropic ocean circulation model O San, AE Staples, Z Wang, T Iliescu Ocean Modelling 40 (2), 120-132, 2011 | 85 | 2011 |

An evolve‐then‐filter regularized reduced order model for convection‐dominated flows D Wells, Z Wang, X Xie, T Iliescu International Journal for Numerical Methods in Fluids 84 (10), 598-615, 2017 | 82 | 2017 |

Variational multiscale proper orthogonal decomposition: Convection-dominated convection-diffusion-reaction equations T Iliescu, Z Wang Mathematics of Computation 82 (283), 1357-1378, 2013 | 76 | 2013 |

Approximate deconvolution reduced order modeling X Xie, D Wells, Z Wang, T Iliescu Computer Methods in Applied Mechanics and Engineering 313, 512-534, 2017 | 74 | 2017 |

Artificial viscosity proper orthogonal decomposition J Borggaard, T Iliescu, Z Wang Mathematical and Computer Modelling 53 (1-2), 269-279, 2011 | 73 | 2011 |

Are the Snapshot Difference Quotients Needed in the Proper Orthogonal Decomposition? T Iliescu, Z Wang SIAM Journal on Scientific Computing 36 (3), A1221-A1250, 2014 | 64 | 2014 |

Non-iterative domain decomposition methods for a non-stationary Stokes–Darcy model with Beavers–Joseph interface condition W Feng, X He, Z Wang, X Zhang Applied Mathematics and Computation 219 (2), 453-463, 2012 | 63 | 2012 |

Structure-preserving Galerkin POD reduced-order modeling of Hamiltonian systems Y Gong, Q Wang, Z Wang Computer Methods in Applied Mechanics and Engineering 315, 780-798, 2017 | 55 | 2017 |

A comparison of neural network architectures for data-driven reduced-order modeling A Gruber, M Gunzburger, L Ju, Z Wang Computer Methods in Applied Mechanics and Engineering 393, 114764, 2022 | 51 | 2022 |

An Efficient Algorithm for Simulating Ensembles of Parameterized Flow Problems M Gunzburger, N Jiang, Z Wang. IMA J. Numer. Anal. 39 (3), 1180-1205, 2019 | 51 | 2019 |

An ensemble algorithm for numerical solutions to deterministic and random parabolic PDEs Y Luo, Z Wang SIAM Journal on Numerical Analysis 56 (2), 859-876, 2018 | 49 | 2018 |

POD/DEIM Reduced-Order Modeling of Time-Fractional Partial Differential Equations with Applications in Parameter Identification H Fu, H Wang, Z Wang Journal of Scientific Computing 74 (1), 220-243, 2018 | 48 | 2018 |

Numerical analysis of the Leray reduced order model X Xie, D Wells, Z Wang, T Iliescu Journal of Computational and Applied Mathematics 328, 12-29, 2018 | 46 | 2018 |

A finite element discretization of the streamfunction formulation of the stationary quasi-geostrophic equations of the ocean EL Foster, T Iliescu, Z Wang Computer Methods in Applied Mechanics and Engineering 261, 105-117, 2013 | 45 | 2013 |

A second-order time-stepping scheme for simulating ensembles of parameterized flow problems M Gunzburger, N Jiang, Z Wang Computational Methods in Applied Mathematics 19 (3), 681-701, 2019 | 43 | 2019 |

A new closure strategy for proper orthogonal decomposition reduced-order models I Akhtar, Z Wang, J Borggaard, T Iliescu Journal of Computational and Nonlinear Dynamics 7 (3), 034503, 2012 | 42 | 2012 |

Approximate partitioned method of snapshots for pod Z Wang, B McBee, T Iliescu Journal of Computational and Applied Mathematics 307, 374-384, 2016 | 39 | 2016 |