{"id":88,"date":"2017-09-07T08:28:21","date_gmt":"2017-09-07T15:28:21","guid":{"rendered":"https:\/\/bio.mech.utah.edu\/?page_id=88"},"modified":"2026-03-26T07:19:03","modified_gmt":"2026-03-26T14:19:03","slug":"publications","status":"publish","type":"page","link":"https:\/\/bio.mech.utah.edu\/index.php\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"

Peer-reviewed Journal papers<\/h2>\n

Google Scholar.<\/a><\/p>\n

Researchgate (publications available for download).<\/a><\/p>\n

The amazing Computational Biomechanics Group students are highlighted in green<\/strong>.<\/span><\/p>\n

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  1. \n
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    1. Elhadidy, M.,<\/span> D’Souza, R. M., <\/strong>Arzani, A.,\u00a0 SLE-FNO: Single-Layer Extensions for Task-Agnostic Continual Learning in Fourier Neural Operators<\/a>, arXiv:2603.20410S, 2026.<\/li>\n
    2. Faroughi, S. A.,\u00a0 Mostajeran, F.,\u00a0 <\/strong>Arzani, A.,\u00a0 Faroughi, S.,\u00a0 Symbolic–KAN: Kolmogorov-Arnold Networks with Discrete Symbolic Structure for Interpretable Learning<\/a>, arXiv:2603.23854, 2026.<\/li>\n
    3. Viknesh, S., Tatari, Y., Christenson, C., <\/span><\/strong>Arzani, A.,\u00a0\u00a0ADAM-SINDy: An Efficient Optimization Framework for Parameterized Nonlinear Dynamical System Identification<\/a>, Physical Review Research<\/em>, 2026.\u00a0 \u00a0Also available on arxiv.<\/a><\/i><\/li>\n
    4. Tatari, Y.,<\/span><\/strong> Nguyen, H.T., Arzani, A. and Newell, P., Investigation of particle transport in geothermal systems using integrated CFD\u2013DEM and data-driven approaches<\/a>, Geothermics<\/em>, 2026.<\/li>\n
    5. Throop, A., Sudbury, N., <\/span><\/strong>Timmins, L. , Baradaran, H., Weiss, J. A.,\u00a0 Arzani, A., Comparative Analysis of Open-Source FEM Solvers for CFD Performance in a Carotid Artery Model<\/a>, Journal of Biomechanical Engineering, 2026. \u00a0 <\/i>\u00a0<\/li>\n
    6. Csala, H,<\/strong>.\u00a0<\/span> Arzani, A., Decomposed sparse modal optimization: Interpretable reduced-order modeling of unsteady flows<\/a>, International Journal of Heat and Fluid Flow, 2026. \u00a0\u00a0<\/i><\/li>\n
    7. Viknesh, S,<\/strong>.\u00a0<\/span> Arzani, A., Differentiable Autoencoding Neural Operator for Interpretable and Integrable Latent Space Modeling<\/a>, arXiv:2510.00233, 2025. <\/i><\/li>\n
    8. Mahmoudi, M., Pogosyan, A., Arzani, A., Nguyen, K. L., Multiscale Coronary Arterial Network Generation and Hemodynamics Using Patient-Specific Fractional Myocardial Blood Volume,<\/a>\u00a0Bioengineering<\/em>, 2025,\u00a0\u00a0<\/i><\/li>\n
    9. Chen, P., Jernigan, S.,\u00a0 Zhao, K. and PJ, G. V. and Saha, M. and Kim, C. and Arzani, A. and Buckner, G. and Hu, J., Image-guided embolization using Ta@Ca-Alg microspheres with optimized mechanical performance<\/a>, Biomaterials Science, 2025. \u00a0<\/i><\/li>\n
    10. Kalajahi, A. P., Csala, H.<\/strong>,<\/span> Mamun, Z. B., Yadav, S., Amili, O., Arzani, A.,\u00a0 D\u2019Souza, R. M., Input parameterized physics informed neural networks for de noising, super-resolution, and imaging artifact mitigation in time resolved three dimensional phase-contrast magnetic resonance imaging<\/a>, Engineering Applications of Artificial Intelligence, 150,\u00a0 2025. \u00a0\u00a0<\/i><\/li>\n
    11. LaBelle, S. A., Soltany Sadrabadi, M.,<\/strong> <\/span>Baek, S., Mofrad, M., Weiss, J. A.,\u00a0 Arzani, A., Multiscale kinematic growth coupled with mechanosensitive systems biology in open-source software<\/a>, Journal of Biomechanical Engineering, 2025. \u00a0\u00a0<\/i><\/li>\n
    12. Csala, H.<\/span>\u00a0<\/strong> Mohan, A.,\u00a0 Livescu, D., Arzani, A., Physics-constrained coupled neural differential equations for one dimensional blood flow modeling<\/a>, Computers in Biology and Medicine, 2025. Also on arxiv.<\/a>\u00a0\u00a0<\/i><\/li>\n
    13. Viknesh, S.,\u00a0 <\/span><\/strong>Tohidi, A., Afghah, F., Stoll, R., Arzani, A., <\/span><\/strong>Role of flow topology in wind-driven wildfire propagation<\/a>,\u00a0 Physics of Fluids<\/em>, 2025.\u00a0 \u00a0Also on arxiv<\/a>.<\/i><\/li>\n
    14. Tatari, Y.<\/span><\/strong>, Smith, T. A., Hu, Y.,\u00a0 Arzani, A.,\u00a0 Optimizing distal and proximal splenic artery embolization with patient-specific computational fluid dynamics<\/a>, Journal of Biomechanics<\/em>, 2024.\u00a0\u00a0<\/i><\/li>\n
    15. Csala, H.<\/span><\/strong>, Amili, O., D’Souza, R. M .,\u00a0 Arzani, A.,\u00a0 A comparison of machine learning methods for recovering noisy and missing 4D flow MRI data<\/a> , International Journal for Numerical Methods in Biomedical Engineering<\/em>, 2024.<\/i><\/li>\n
    16. Arzani, A., Yuan, L., Newell, P., Wang, B., Interpreting and generalizing deep learning in physics-based problems with functional linear models<\/a>, Engineering with Computers<\/em>, 2024.\u00a0 Also available on arxiv.<\/a><\/em><\/i><\/li>\n
    17. Yeh, H. P.<\/span><\/strong>, Bayat, M., Arzani, A., Hattel, J. H. Accelerated Process Parameter Selection of Polymer-based Selective Laser Sintering via Hybrid Physics-informed Neural Network and Finite Element Surrogate Modelling<\/a>, Applied Mathematical Modelling, 2024.\u00a0<\/i><\/li>\n
    18. Csala, H.<\/span><\/strong>, Mohan, A. T., Livescu, D., Arzani, A., Modeling Coupled 1D PDEs of Cardiovascular Flow with Spatial Neural ODE<\/a>, NeurIPS<\/em>, 2023.\u00a0<\/i><\/li>\n
    19. Pirola, S., Arzani, A., Chiastra, C., Sturla, G., Editorial: Image-based computational approaches for personalized cardiovascular medicine: improving clinical applicability and reliability through medical imaging and experimental data<\/a>, Frontiers in Medical Technology<\/em>, 2023.<\/li>\n
    20. Aliakbari, M., Soltany Sadrabadi, M.<\/strong>, <\/span>Vadasz, P., Arzani, A., Ensemble physics informed neural networks: A framework to improve inverse transport modeling in heterogeneous domains<\/a>, Physics of Fluids, 2023.\u00a0<\/i><\/li>\n
    21. \u00a0Arzani, A., Cassel, K. W., D’Souza, R. M., Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation<\/a>, Journal of Computational Physics, 2023.\u00a0<\/i><\/li>\n
    22. Csala, H.<\/strong>, <\/span>Dawson, S., Arzani, A.,\u00a0 Comparing different nonlinear dimensionality reduction techniques for data-driven unsteady fluid flow modeling,<\/a> Physics of Fluids,, 2022.\u00a0<\/i><\/li>\n
    23. Aliakbari, M., Mahmoudi, M.<\/strong>, <\/span>Vadasz, P., Arzani, A., Predicting high-fidelity multiphysics data from low-fidelity fluid flow and transport solvers using physics-informed neural networks<\/a>, International Journal of Heat and Fluid Flow<\/em>, 2022.<\/li>\n
    24. Mahmoudi, M.<\/strong>, Jennings, C.<\/strong><\/span>, Pereira, K., Hall, A., Arzani, A., Guiding the prostatic artery embolization procedure with computational fluid dynamics<\/a>, Journal of Biomechanical Engineering<\/em>, 2022.<\/li>\n
    25. \u00a0Arzani, A., Wang, J. X., Sacks, M. S., Shadden, S. C. Machine learning for cardiovascular biomechanics modeling: challenges and beyond<\/a>,<\/a> Annals of Biomedical Engineering<\/em>,, 2022.<\/em><\/li>\n
    26. Baek, S.,\u00a0 Arzani, A., Current state-of-the-art and utilities of machine learning for detection, monitoring, growth prediction, rupture risk assessment, and post-surgical management of abdominal aortic aneurysms,<\/a> Applications in Engineering Science<\/em>, 2022.<\/em><\/li>\n
    27. Soltany Sadrabadi, M<\/strong>.<\/span>, Eskandari, M., Feigenbaum, H. P., Arzani, A.,\u00a0 Local and global growth and remodeling in calcific aortic valve disease and aging<\/a>, Journal of Biomechanics<\/em>, 128(9), 110773, 2021.<\/em><\/li>\n
    28. Arzani, A., Wang, J. X., D’Souza, R. M. Uncovering near-wall blood flow from sparse data with physics-informed neural networks<\/a>, Physics of Fluids<\/em>, 33, 071905, 2021. <\/em>Editor’s Featured Article.<\/span> Also available on arxiv.<\/a><\/em><\/li>\n
    29. Habibi, M<\/strong>.<\/span>, D’Souza, R. M., Dawson, S. T. M., Arzani, A. Integrating multi-fidelity blood flow data with reduced-order data assimilation<\/a>, Computers in Biology and Medicine, <\/em>14, 104566, 2021<\/em>.<\/a>\u00a0<\/em><\/li>\n
    30. Arzani, A., Dawson, S. T. M., Data-driven cardiovascular flow modeling: examples and opportunities<\/a>, Journal of the Royal Society Interface<\/em>, 18, 20200802, 2021. <\/em>Also available on arxiv.<\/a>\u00a0<\/em><\/li>\n
    31. Soltany Sadrabadi, M.<\/span><\/strong>, Hedayat, M., Borazjani, I., Arzani, A. Fluid-structure coupled biotransport processes in aortic valve disease,<\/a> Journal of Biomechanics, 117(5),110239,\u00a0 2021.<\/em><\/li>\n
    32. Meschi, S. S, Farghadan, A.<\/span><\/strong>, Arzani, A. Flow topology and targeted drug delivery in cardiovascular disease<\/a>, Journal of Biomechanics (invited special issue), 19, 110307, 2021.<\/em><\/li>\n
    33. Mahmoudi, M., Farghadan, A., McConnell, D. R<\/strong>.<\/span>, Barker, A. J., Wentzel, J. J., Budoff, M. J., Arzani, A., The story of wall shear stress in coronary artery atherosclerosis: biochemical transport and mechanotransduction<\/a>, Journal of Biomechanical Engineering, 143(4): 041002, 2021<\/em>.<\/li>\n
    34. Fathi, M. F., Perez-Raya, I., Baghaie, A., Berg, P., Janiga, G., Arzani, A., D\u2019Souza, R. M., Super-resolution and Denoising of 4D-Flow MRI Using Physics-Informed Deep Neural Nets<\/a>, Computer Methods and Programs in Biomedicine, 197, 105729, 2020.<\/em><\/li>\n
    35. Habibi, H<\/span>.<\/strong>, Dawson, S. T. M., Arzani, A., Data-Driven Pulsatile Blood Flow Physics with Dynamic Mode Decomposition<\/a>, Fluids, 5(3). 111, 2020.<\/em><\/li>\n
    36. Farghadan, A<\/strong>.<\/span>, Poorbahrami, K., Jalal, S., Oakes, J. M., Coletti, F., Arzani, A., Particle transport and deposition correlation with near-wall flow characteristic under inspiratory airflow in lung airways<\/a>, Computers in Biology and Medicine<\/em>, 120. 103703, 2020.<\/em><\/li>\n
    37. Arzani, A., Coronary artery plaque growth: a two-way coupled shear stress driven model<\/a>, International Journal for Numerical Methods in Biomedical Engineering<\/em>, 36, e3293, 2020.<\/em><\/li>\n
    38. Farghadan, A.<\/span><\/strong>, Coletti, F., Arzani, A., Topological analysis of particle transport in lung airways: predicting particle source and destination<\/a>, Computers in Biology and Medicine, 115. 103497, 2019<\/em><\/li>\n
    39. Reza, M. M. S.<\/span><\/strong>, Arzani, A.,\u00a0 A critical comparison of different residence time measures in aneurysms<\/a>,\u00a0 Journal of Biomechanics<\/em>, 88. 122-129, 2019.<\/em><\/li>\n
    40. Farghadan, A.<\/strong>,<\/span> Arzani, A.,\u00a0The combined effect of wall shear stress topology and magnitude on cardiovascular mass transport<\/a>,\u00a0International Journal of Heat and Mass Transfer<\/em>,\u00a0131<\/strong>, 2019.<\/em><\/li>\n
    41. Arzani, A.,\u00a0Accounting for residence-time in blood rheology models: do we really need non-Newtonian blood flow modeling in large arteries?<\/a>,\u00a0Journal of the Royal Society Interface<\/em>, 15<\/strong>(146), 2018.<\/em><\/li>\n
    42. Hansen, K. B., Arzani, A. and Shadden, S. C.,\u00a0Finite element modeling of near\u2010wall mass transport in cardiovascular flows<\/a>,\u00a0International Journal for Numerical Methods in Biomedical Engineering<\/em>, 35<\/strong>, 2019<\/em>.<\/li>\n
    43. Arzani, A., Shadden, S. C., Wall shear stress fixed points in cardiovascular fluid mechanics<\/a>, Journal of Biomechanics, 73<\/b>, 145-152, 2018<\/em>.<\/li>\n
    44. Arzani, A., Mofrad, M. R. K.,\u00a0A strain-based finite element model for calcification progression in aortic valves<\/a>, Journal of Biomechanics, <\/em>65<\/strong>, 216-220, 2017.\u00a0<\/li>\n
    45. Arzani, A., Masters, K. S., Mofrad, M. R. K., Multiscale systems biology model of calcific aortic valve disease progression<\/a>, \u00a0ACS Biomaterials Science & Engineering<\/em>, 3<\/strong>(11), 2922-2933, 2017.<\/li>\n
    46. Arzani, A., Gambaruto, A. M., Chen, G. and Shadden, S. C.,\u00a0Wall shear stress exposure time: A Lagrangian measure of near-wall stagnation and concentration in cardiovascular flows<\/a>,\u00a0Biomechanics and Modeling in Mechanobiology<\/em>,\u00a016<\/strong>(3), 787\u2013803, 2017.<\/li>\n
    47. Arzani, A., Gambaruto, A. M., Chen, G. and Shadden, S. C.,\u00a0Lagrangian wall shear stress structures and near wall transport in high Schmidt aneurysmal flows<\/a>,\u00a0Journal of Fluid Mechanics<\/em>,\u00a0790<\/strong>, 158-172, 2016.<\/li>\n
    48. Arzani, A. and Shadden, S. C. Characterizations and correlations of wall shear stress in aneurysmal flow<\/a>,\u00a0Journal of Biomechanical Engineering<\/em>\u00a0138<\/strong>(1), 014503-1-10, 2015.<\/li>\n
    49. Hansen, K. B., Arzani, A. and Shadden, S. C., Mechanical platelet activation potential in abdominal aortic aneurysms<\/a>,\u00a0Journal of Biomechanical Engineering<\/em>,\u00a0137<\/strong>(4), 041005-1-8, 2015.<\/li>\n
    50. Shadden, S. C. and Arzani, A., Lagrangian postprocessing of computational hemodynamics<\/a>,\u00a0Annals of Biomedical Engineering<\/em>,\u00a043<\/strong>(1), 41-58, 2015.<\/li>\n
    51. Arzani, A., Suh, G. Y., Dalman, R. L. and Shadden, S. C., A longitudinal comparison of hemodynamics and intraluminal thrombus deposition in abdominal aortic aneurysms<\/a>,\u00a0American Journal of Physiology- Heart and Circulatory Physiology<\/em>,\u00a0307<\/strong>(12), H1786-H1795, 2014.<\/li>\n
    52. Arzani, A., Les, A. S., Dalman, R. L. and Shadden, S. C., Effect of exercise on patient specific abdominal aortic aneurysm flow topology and mixing<\/a>,\u00a0International Journal for Numerical Methods in Biomedical Engineering<\/em>,\u00a030<\/strong>(2), 280-295, 2014.<\/li>\n
    53. Steinman, D. A., Hoi, Y., Fahy, P., Morris, L., Walsh, M. T., Aristokleous, N., Anayiotos, A. S., Papaharilaou, Y., Arzani, A., Shadden, S. C., et al.,\u00a0Variability of computational fluid dynamics solutions for pressure and flow in a giant aneurysm: The ASME 2012 Summer Bioengineering Conference CFD Challenge<\/a>,\u00a0Journal of Biomechanical Engineering<\/em>,\u00a0135<\/strong>(2), 021016-1-13, 2013.<\/li>\n
    54. Arzani, A. and Shadden, S. C.,\u00a0Characterization of the transport topology in patient-specific abdominal aortic aneurysm models<\/a>,\u00a0Physics of Fluids<\/em>,\u00a024<\/strong>(8), 081901-1-16, 2012.<\/li>\n
    55. Arzani, A., Dyverfeldt, P., Ebbers, T. and Shadden, S. C.,\u00a0In vivo validation of numerical prediction for turbulence intensity in an aortic coarctation<\/a>,\u00a0Annals of Biomedical Engineering<\/em>,\u00a040<\/strong>(4), 860-870, 2012.<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n
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      1. \u00a0<\/li>\n<\/ol>\n\n\n

        <\/p>\n","protected":false},"excerpt":{"rendered":"

        Peer-reviewed Journal papers Google Scholar. Researchgate (publications available for download). The amazing Computational Biomechanics Group students are highlighted in green. Elhadidy, M., D’Souza, R. M., Arzani, A.,\u00a0 SLE-FNO: Single-Layer Extensions for Task-Agnostic Continual Learning in Fourier Neural Operators, arXiv:2603.20410S, 2026.<\/p>\n","protected":false},"author":4,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-88","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/bio.mech.utah.edu\/index.php\/wp-json\/wp\/v2\/pages\/88","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bio.mech.utah.edu\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bio.mech.utah.edu\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bio.mech.utah.edu\/index.php\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/bio.mech.utah.edu\/index.php\/wp-json\/wp\/v2\/comments?post=88"}],"version-history":[{"count":98,"href":"https:\/\/bio.mech.utah.edu\/index.php\/wp-json\/wp\/v2\/pages\/88\/revisions"}],"predecessor-version":[{"id":1197,"href":"https:\/\/bio.mech.utah.edu\/index.php\/wp-json\/wp\/v2\/pages\/88\/revisions\/1197"}],"wp:attachment":[{"href":"https:\/\/bio.mech.utah.edu\/index.php\/wp-json\/wp\/v2\/media?parent=88"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}