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:

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

Robust Physics Informed Neural Networks

Robust Variational Physics-Informed Neural Networks

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

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

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

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

Title

Journal

Author(s)

Publication Date

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

Journal of Computational Science

Marcin Skotniczny

Anna Paszyńska

Sergio Rojas

Maciej Paszyński

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

Marcin Łoś

Leszek Siwik

Maciej Woźniak

Dominik Gryboś

Paweł Maczuga

...

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

Magdalena Pabisz

Judit Muñoz-Matute

Maciej Paszyński

2024/2/3

Robust Physics Informed Neural Networks

arXiv preprint arXiv:2401.02300

Marcin Łoś

Maciej Paszyński

2024/1/4

Robust Variational Physics-Informed Neural Networks

Computer Methods in Applied Mechanics and Engineering

Sergio Rojas

Paweł Maczuga

Judit Muñoz-Matute

David Pardo

Maciej Paszyński

2024/5/15

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

arXiv preprint arXiv:2307.07647

Maciej Sikora

Patryk Krukowski

Anna Paszynska

Maciej Paszynski

2023/7/14

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

Computers & Mathematics with Applications

Marcin Łoś

Maciej Woźniak

Keshav Pingali

Luis Emilio Garcia Castillo

Julen Alvarez-Aramberri

...

2023/12/1

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

Tomasz Służalec

Maciej Paszyński

2023/6/26

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

arXiv preprint arXiv:2310.03755

Paweł Maczuga

Maciej Skoczeń

Przemysław Rożnawski

Filip Tłuszcz

Marcin Szubert

...

2023/9/24

The Computational Planet

Sergey V Kovalchuk

Clélia de Mulatier

Derek Groen

Maciej Paszyński

Valeria V Krzhizhanovskaya

...

2023/7/14

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

Computer Methods in Applied Mechanics and Engineering

Tomasz Służalec

Mateusz Dobija

Anna Paszyńska

Ignacio Muga

Marcin Łoś

...

2023/6/1

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

Journal of Computational and Applied Mathematics

Marcin Łoś

Maciej Paszyński

2023/8/15

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

Jiří Mikyška

Clélia de Mulatier

Maciej Paszynski

Valeria V Krzhizhanovskaya

Jack J Dongarra

...

2023/6/29

Cloud-native alternating directions solver for isogeometric analysis

Future Generation Computer Systems

Grzegorz Gurgul

Bartosz Baliś

Maciej Paszyński

2023/3/1

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

Computers & Mathematics with Applications

Victor M Calo

Pouria Behnoudfar

M Łoś

M Paszyński

2023/7/15

The first scientiffic evidence for the hail cannon

Krzysztof Misan

Maciej Kozieja

Marcin Łoś

Dominik Gryboś

Jacek Leszczyński

...

2023/6/26

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

Maciej Paszyński

2023/1/27

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

Computers & Mathematics with Applications

Tomasz Służalec

Rafał Grzeszczuk

Sergio Rojas

Witold Dzwinel

Maciej Paszyński

2023/7/15

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

Computers & Mathematics with Applications

Marcin Łoś

Paulina Sepúlveda

Maciej Sikora

Maciej Paszyński

2023/12/15

Vecpar–A Framework for Portability and Parallelization

Jiří Mikyška

Beomki Yeo

Georgiana Mania

Michael Kuhn

Peter Sloot

...

2023

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

Co-Authors

academic-engine