| A point-cloud deep learning framework for prediction of fluid flow fields on irregular geometries A Kashefi, D Rempe, LJ Guibas Physics of Fluids 33 (2), 027104, 2021 | 179 | 2021 |
| Chatgpt for programming numerical methods A Kashefi, T Mukerji Journal of Machine Learning for Modeling and Computing, 2023 | 71 | 2023 |
| Physics-informed PointNet: A deep learning solver for steady-state incompressible flows and thermal fields on multiple sets of irregular geometries A Kashefi, T Mukerji Journal of Computational Physics 468, 111510, 2022 | 64 | 2022 |
| Point-cloud deep learning of porous media for permeability prediction A Kashefi, T Mukerji Physics of Fluids 33 (9), 097109, 2021 | 32 | 2021 |
| A finite-element coarse-grid projection method for incompressible flow simulations A Kashefi, AE Staples Advances in Computational Mathematics 44, 1063-1090, 2018 | 17 | 2018 |
| Prediction of fluid flow in porous media by sparse observations and physics-informed PointNet A Kashefi, T Mukerji Neural Networks, 2023 | 14 | 2023 |
| Multidimensional modeling of the stenosed carotid artery: A novel CAD approach accompanied by an extensive lumped model A Kashefi, M Mahdinia, B Firoozabadi, M Amirkhosravi, G Ahmadi, ... Acta Mechanica Sinica 30, 259-273, 2014 | 14 | 2014 |
| Coarse grid projection methodology: a partial mesh refinement tool for incompressible flow simulations A Kashefi Bulletin of the Iranian Mathematical Society 46, 177-181, 2020 | 7 | 2020 |
| A coarse grid projection method for accelerating free and forced convection heat transfer computations A Kashefi Results in Mathematics 75, 1-24, 2020 | 6 | 2020 |
| A coarse-grid incremental pressure projection method for accelerating low Reynolds number incompressible flow simulations A Kashefi Iran Journal of Computer Science 3 (1), 13-23, 2020 | 5 | 2020 |
| A coarse-grid projection method for accelerating incompressible MHD flow simulations A Kashefi Engineering with Computers 38 (2), 1539-1553, 2022 | 3 | 2022 |
| Physics-informed PointNet: On how many irregular geometries can it solve an inverse problem simultaneously? Application to linear elasticity A Kashefi, L Guibas, T Mukerji Journal of Machine Learning for Modeling and Computing, 2023 | 2 | 2023 |
| Acceleration of incremental-pressure-correction incompressible flow computations using a coarse-grid projection method A Kashefi, A Staples APS Division of Fluid Dynamics Meeting Abstracts, 2016 | 2 | 2016 |
| A coarse-grid-projection acceleration method for finite-element incompressible flow computations A Kashefi, A Staples APS Division of Fluid Dynamics Meeting Abstracts, 2015 | 1 | 2015 |
| A novel Fourier neural operator framework for classification of multi-sized images: Application to 3D digital porous media A Kashefi, T Mukerji arXiv preprint arXiv:2402.11568, 2024 | | 2024 |
| ChatGPT for Programming Numerical Problems of Fluid Mechanics A Kashefi, T Mukerji Bulletin of the American Physical Society, 2023 | | 2023 |
| Deep Learning Algorithms for Computational Mechanics on Irregular Geometries A Kashefi Stanford University, 2023 | | 2023 |
| Physics-informed PointNet for predicting thermal fields of natural convection on multiple sets of irregular geometries A Kashefi, T Mukerji Fall Meeting 2022, 2022 | | 2022 |
| Fluid Flow Prediction in Porous Media using Sparse Data and Physics-Informed PointNet A Kashefi, T Mukerji Bulletin of the American Physical Society, 2022 | | 2022 |
| A point-cloud deep learning strategy for predicting permeability of porous media A Kashefi, T Mukerji AGU Fall Meeting 2021, 2021 | | 2021 |
Leonidas GuibasProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
