Peer-reviewed Journal papers

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Researchgate (publications available for download).

The amazing Computational Biomechanics Group students are highlighted in green.

    1. Csala, H.  Mohan, A.,  Livescu, D., Arzani, A., Physics-constrained coupled neural differential equations for one dimensional blood flow modeling, arXiv preprint arXiv:2411.05631, 2024.  
    2. Viknesh, S.,  Tohidi, A., Afghah, F., Stoll, R., Arzani, A.,Role of flow topology in wind-driven wildfire propagation, arXiv preprint arXiv:2411.04007, 2024.  
    3. Viknesh, S., Tatari, Y., Arzani, A.,  ADAM-SINDy: An Efficient Optimization Framework for Parameterized Nonlinear Dynamical System Identification, arXiv preprint arXiv:2410., 2024.  
    4. Tatari, Y., Smith, T. A., Hu, Y.,  Arzani, A.,  Optimizing distal and proximal splenic artery embolization with patient-specific computational fluid dynamics, Journal of Biomechanics, 2024.  
    5. Csala, H., Amili, O., D’Souza, R. M .,  Arzani, A.,  A comparison of machine learning methods for recovering noisy and missing 4D flow MRI data , International Journal for Numerical Methods in Biomedical Engineering, 2024.
    6. Arzani, A., Yuan, L., Newell, P., Wang, B., Interpreting and generalizing deep learning in physics-based problems with functional linear models, Engineering with Computers, 2024.  Also available on arxiv.
    7. Yeh, H. P., 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, Applied Mathematical Modelling, 2024. 
    8. Csala, H., Mohan, A. T., Livescu, D., Arzani, A., Modeling Coupled 1D PDEs of Cardiovascular Flow with Spatial Neural ODE, NeurIPS, 2023. 
    9. 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, Frontiers in Medical Technology, 2023.
    10. Aliakbari, M., Soltany Sadrabadi, M., Vadasz, P., Arzani, A., Ensemble physics informed neural networks: A framework to improve inverse transport modeling in heterogeneous domains, Physics of Fluids, 2023. 
    11.  Arzani, A., Cassel, K. W., D’Souza, R. M., Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation, Journal of Computational Physics, 2023. 
    12. Csala, H., Dawson, S., Arzani, A.,  Comparing different nonlinear dimensionality reduction techniques for data-driven unsteady fluid flow modeling, Physics of Fluids,, 2022. 
    13. Aliakbari, M., Mahmoudi, M., Vadasz, P., Arzani, A., Predicting high-fidelity multiphysics data from low-fidelity fluid flow and transport solvers using physics-informed neural networks, International Journal of Heat and Fluid Flow, 2022.
    14. Mahmoudi, M., Jennings, C., Pereira, K., Hall, A., Arzani, A., Guiding the prostatic artery embolization procedure with computational fluid dynamics, Journal of Biomechanical Engineering, 2022.
    15.  Arzani, A., Wang, J. X., Sacks, M. S., Shadden, S. C. Machine learning for cardiovascular biomechanics modeling: challenges and beyond, Annals of Biomedical Engineering,, 2022.
    16. Baek, S.,  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, Applications in Engineering Science, 2022.
    17. Soltany Sadrabadi, M., Eskandari, M., Feigenbaum, H. P., Arzani, A.,  Local and global growth and remodeling in calcific aortic valve disease and aging, Journal of Biomechanics, 128(9), 110773, 2021.
    18. Arzani, A., Wang, J. X., D’Souza, R. M. Uncovering near-wall blood flow from sparse data with physics-informed neural networks, Physics of Fluids, 33, 071905, 2021. Editor’s Featured Article. Also available on arxiv.
    19. Habibi, M., D’Souza, R. M., Dawson, S. T. M., Arzani, A. Integrating multi-fidelity blood flow data with reduced-order data assimilation, Computers in Biology and Medicine, 14, 104566, 2021. 
    20. Arzani, A., Dawson, S. T. M., Data-driven cardiovascular flow modeling: examples and opportunities, Journal of the Royal Society Interface, 18, 20200802, 2021. Also available on arxiv. 
    21. Soltany Sadrabadi, M., Hedayat, M., Borazjani, I., Arzani, A. Fluid-structure coupled biotransport processes in aortic valve disease, Journal of Biomechanics, 117(5),110239,  2021.
    22. Meschi, S. S, Farghadan, A., Arzani, A. Flow topology and targeted drug delivery in cardiovascular disease, Journal of Biomechanics (invited special issue), 19, 110307, 2021.
    23. Mahmoudi, M., Farghadan, A., McConnell, D. R., 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, Journal of Biomechanical Engineering, 143(4): 041002, 2021.
    24. Fathi, M. F., Perez-Raya, I., Baghaie, A., Berg, P., Janiga, G., Arzani, A., D’Souza, R. M., Super-resolution and Denoising of 4D-Flow MRI Using Physics-Informed Deep Neural Nets, Computer Methods and Programs in Biomedicine, 197, 105729, 2020.
    25. Habibi, H., Dawson, S. T. M., Arzani, A., Data-Driven Pulsatile Blood Flow Physics with Dynamic Mode Decomposition, Fluids, 5(3). 111, 2020.
    26. Farghadan, A., 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, Computers in Biology and Medicine, 120. 103703, 2020.
    27. Arzani, A., Coronary artery plaque growth: a two-way coupled shear stress driven model, International Journal for Numerical Methods in Biomedical Engineering, 36, e3293, 2020.
    28. Farghadan, A., Coletti, F., Arzani, A., Topological analysis of particle transport in lung airways: predicting particle source and destination, Computers in Biology and Medicine, 115. 103497, 2019
    29. Reza, M. M. S., Arzani, A.,  A critical comparison of different residence time measures in aneurysms,  Journal of Biomechanics, 88. 122-129, 2019.
    30. Farghadan, A., Arzani, A., The combined effect of wall shear stress topology and magnitude on cardiovascular mass transport, International Journal of Heat and Mass Transfer, 131, 2019.
    31. Arzani, A., Accounting for residence-time in blood rheology models: do we really need non-Newtonian blood flow modeling in large arteries?, Journal of the Royal Society Interface, 15(146), 2018.
    32. Hansen, K. B., Arzani, A. and Shadden, S. C., Finite element modeling of near‐wall mass transport in cardiovascular flows, International Journal for Numerical Methods in Biomedical Engineering, 35, 2019.
    33. Arzani, A., Shadden, S. C., Wall shear stress fixed points in cardiovascular fluid mechanics, Journal of Biomechanics, 73, 145-152, 2018.
    34. Arzani, A., Mofrad, M. R. K., A strain-based finite element model for calcification progression in aortic valves, Journal of Biomechanics, 65, 216-220, 2017. 
    35. Arzani, A., Masters, K. S., Mofrad, M. R. K., Multiscale systems biology model of calcific aortic valve disease progression,  ACS Biomaterials Science & Engineering, 3(11), 2922-2933, 2017.
    36. Arzani, A., Gambaruto, A. M., Chen, G. and Shadden, S. C., Wall shear stress exposure time: A Lagrangian measure of near-wall stagnation and concentration in cardiovascular flows, Biomechanics and Modeling in Mechanobiology, 16(3), 787–803, 2017.
    37. Arzani, A., Gambaruto, A. M., Chen, G. and Shadden, S. C., Lagrangian wall shear stress structures and near wall transport in high Schmidt aneurysmal flows, Journal of Fluid Mechanics, 790, 158-172, 2016.
    38. Arzani, A. and Shadden, S. C. Characterizations and correlations of wall shear stress in aneurysmal flow, Journal of Biomechanical Engineering 138(1), 014503-1-10, 2015.
    39. Hansen, K. B., Arzani, A. and Shadden, S. C., Mechanical platelet activation potential in abdominal aortic aneurysms, Journal of Biomechanical Engineering, 137(4), 041005-1-8, 2015.
    40. Shadden, S. C. and Arzani, A., Lagrangian postprocessing of computational hemodynamics, Annals of Biomedical Engineering, 43(1), 41-58, 2015.
    41. 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, American Journal of Physiology- Heart and Circulatory Physiology, 307(12), H1786-H1795, 2014.
    42. 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, International Journal for Numerical Methods in Biomedical Engineering, 30(2), 280-295, 2014.
    43. 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., Variability of computational fluid dynamics solutions for pressure and flow in a giant aneurysm: The ASME 2012 Summer Bioengineering Conference CFD Challenge, Journal of Biomechanical Engineering, 135(2), 021016-1-13, 2013.
    44. Arzani, A. and Shadden, S. C., Characterization of the transport topology in patient-specific abdominal aortic aneurysm models, Physics of Fluids, 24(8), 081901-1-16, 2012.
    45. Arzani, A., Dyverfeldt, P., Ebbers, T. and Shadden, S. C., In vivo validation of numerical prediction for turbulence intensity in an aortic coarctation, Annals of Biomedical Engineering, 40(4), 860-870, 2012.
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