Maciej Paszynski

About Maciej Paszynski

Maciej Paszynski, With an exceptional h-index of 27 and a recent h-index of 13 (since 2020), a distinguished researcher at Akademia Górniczo-Hutnicza, specializes in the field of isogeometric analysis, hp-adaptive finite element method, computational science, neural networks.

His recent articles reflect a diverse array of research interests and contributions to the field:

Robust Physics Informed Neural Networks

Robust Variational Physics-Informed Neural Networks

Complexity of direct and iterative solvers on space–time formulations and time-marching schemes for h-refined grids towards singularities

Shock waves generators: From prevention of hail storms to reduction of the smog in urban areas-experimental verification and numerical simulations

Augmenting MRI scan data with real-time predictions of glioblastoma brain tumor evolution using exponential time integrators

Solver algorithm for stabilized space-time formulation of advection-dominated diffusion problem

Fast parallel IGA-ADS solver for time-dependent Maxwell's equations

Physics Informed Neural Network Code for 2D Transient Problems (PINN-2DT) Compatible with Google Colab

Maciej Paszynski Information

University

Position

Department of Computer Science and

Citations(all)

2514

Citations(since 2020)

827

Cited By

2196

hIndex(all)

27

hIndex(since 2020)

13

i10Index(all)

64

i10Index(since 2020)

27

Email

University Profile Page

Google Scholar

Maciej Paszynski Skills & Research Interests

isogeometric analysis

hp-adaptive finite element method

computational science

neural networks

Top articles of Maciej Paszynski

Robust Physics Informed Neural Networks

arXiv preprint arXiv:2401.02300

2024/1/4

Robust Variational Physics-Informed Neural Networks

Computer Methods in Applied Mechanics and Engineering

2024/5/15

Complexity of direct and iterative solvers on space–time formulations and time-marching schemes for h-refined grids towards singularities

Journal of Computational Science

2024/3/1

Shock waves generators: From prevention of hail storms to reduction of the smog in urban areas-experimental verification and numerical simulations

Journal of Computational Science

2024/2/29

Augmenting MRI scan data with real-time predictions of glioblastoma brain tumor evolution using exponential time integrators

arXiv preprint arXiv:2402.02273

2024/2/3

Solver algorithm for stabilized space-time formulation of advection-dominated diffusion problem

Computers & Mathematics with Applications

2023/12/15

Fast parallel IGA-ADS solver for time-dependent Maxwell's equations

Computers & Mathematics with Applications

2023/12/1

Physics Informed Neural Network Code for 2D Transient Problems (PINN-2DT) Compatible with Google Colab

arXiv preprint arXiv:2310.03755

2023/9/24

Stability of non-linear flow in heterogeneous porous media simulations using higher order and continuity basis functions

Journal of Computational and Applied Mathematics

2023/8/15

A Kronecker product linear-cost solver for the high-order generalized-α method for multi-dimensional hyperbolic systems

Computers & Mathematics with Applications

2023/7/15

Quasi-optimal hp-finite element refinements towards singularities via deep neural network prediction

Computers & Mathematics with Applications

2023/7/15

Physics Informed Neural Networks with strong and weak residuals for advection-dominated diffusion problems

arXiv preprint arXiv:2307.07647

2023/7/14

Anna Paszynska
Anna Paszynska

H-Index: 7

Maciej Paszynski
Maciej Paszynski

H-Index: 16

The Computational Planet

2023/7/14

Computational Science–ICCS 2023: 23rd International Conference, Prague, Czech Republic, July 3–5, 2023, Proceedings, Part IV

2023/6/29

Maciej Paszynski
Maciej Paszynski

H-Index: 16

The first scientiffic evidence for the hail cannon

2023/6/26

Influence of activation functions on the convergence of physics-informed neural networks for 1d wave equation

2023/6/26

Fast Solver for Advection Dominated Diffusion Using Residual Minimization and Neural Networks

2023/6/26

Automatic stabilization of finite-element simulations using neural networks and hierarchical matrices

Computer Methods in Applied Mechanics and Engineering

2023/6/1

Cloud-native alternating directions solver for isogeometric analysis

Future Generation Computer Systems

2023/3/1

Object-oriented software system that performs FPM simulation in the area with moving boundary, and its application to the blood flow problem

Computer Assisted Methods in Engineering and Science

2023/1/27

See List of Professors in Maciej Paszynski University(Akademia Górniczo-Hutnicza)

Co-Authors

academic-engine