Publications

Mac Grory, B., Randles, A., Urick, D. M., Schwartz, F. R., Hasan, D., & Calabrese, E. D. (2026). Photon-Counting CT for Evaluation of Coiled Intracranial Aneurysms. AJNR Am J Neuroradiol, 47(4), 912–919. https://doi.org/10.3174/ajnr.A9015

Martin, A., Ladd, W., Wu, R., & Randles, A. (2026). High-throughput adaptive physics refinement for tissue-scale adhesive dynamics. Journal of Computational Science, 95. https://doi.org/10.1016/j.jocs.2026.102812

Tanade, C., Mavi, J. K., Ferreira, G., Schwaller, S., & Randles, A. (2026). Optimizing Non-invasive Fractional Flow Reserve Estimation with Machine Learning-Enhanced 1D Hemodynamic Modeling. Cardiovascular Engineering and Technology. https://doi.org/10.1007/s13239-026-00836-y

Tanade, C., Jensen, C. W., Ferreira, G., & Randles, A. (2026). Real-Time Peripheral Revascularization Planning in Chronic Limb Threatening Ischemia Using HarVI: A Digital Twin Approach. Cardiovascular Engineering and Technology. https://doi.org/10.1007/s13239-026-00825-1

Wu, R., Ferreira, G., Khan, N. S., Mahmud, S. T., Stoop, J., Sohn, L. L., … Randles, A. (2026). Digital twins and digital models of the human circulatory system. Nature Reviews Bioengineering. https://doi.org/10.1038/s44222-026-00427-5

Saxena, Y., Riley, L., Wu, R., Kabir, M. S., Randles, A., & Segura, T. (2025). 3D pore shape is predictable in randomly packed particle systems. Matter, 102493. https://doi.org/10.1016/j.matt.2025.102493

Ghorbannia, A., Tanade, C., Yousef, A., Khan, N. S., Vardhan, M., Chi, J. T., … Randles, A. (2025). Simulation-based machine learning for real-time assessment of side-branch hemodynamics in coronary bifurcation lesions. International Journal of High Performance Computing Applications, 39(5), 678–691. https://doi.org/10.1177/10943420251351125

Khan, N. S., Tanade, C., Geddes, J., & Randles, A. (2025). Establishing hemodynamic convergence framework for coronary digital twins under realistic dynamic heart rates. Physics of Fluids, 37(9). https://doi.org/10.1063/5.0287796

Geddes, J. R., Jensen, C. W., Tanade, C., Ghorbannia, A., Fudim, M., Patel, M. R., & Randles, A. (2025). Digital twins for noninvasively measuring predictive markers of right heart failure. NPJ Digit Med, 8(1), 545. https://doi.org/10.1038/s41746-025-01920-8

Martin, A., Yousef, A., Liu, G., Ladd, W., Georgiadou, A., Stoop, J., & Randles, A. (2025). Performance Portability Evaluation of Fluid-Structure Interaction Simulations on Heterogeneous Platforms. In https://ieeexplore.ieee.org/xpl/conhome/11008903/proceeding (pp. 1–11). Hamburg, Germany: IEEE.

Aran, K., Li, J., Randles, A., & Wan, Y. (2025). Meet the winners of the 2024 Sony Women in Technology Award. Nature Reviews Electrical Engineering, 2(5), 297–301. https://doi.org/10.1038/s44287-025-00171-9

Martin, A., Nezdyur, M., Tanade, C., & Randles, A. (2025). Establishing a massively parallel computational model of the adaptive immune response. Journal of Computational Science, 87. https://doi.org/10.1016/j.jocs.2025.102555

Tanade, C., & Randles, A. (2025). Real-time virtual intervention for simple and serial coronary artery disease using the HarVI framework. Journal of Computational Science, 87. https://doi.org/10.1016/j.jocs.2025.102570

Geddes, J. R., King, T. D., Tanade, C., Ladd, W., Khan, N. S., & Randles, A. (2025). Impact of inlet velocity waveform shape on hemodynamics. Journal of Computational Science, 87. https://doi.org/10.1016/j.jocs.2025.102579

Deelman, E., Dongarra, J., Hendrickson, B., Randles, A., Reed, D., Seidel, E., & Yelick, K. (2025). High-performance computing at a crossroads. Science (New York, N.Y.), 387(6736), 829–831. https://doi.org/10.1126/science.adu0801

Deelman, E., Dongarra, J., Hendrickson, B., Randles, A., Reed, D., Seidel, E., & Yelick, K. (2025). Retrospective on the Lax Report: Then and Now. Computing in Science and Engineering. https://doi.org/10.1109/MCSE.2025.3647733

Mahmud, S. T., Ma, W., Thomsen, T., Chen, C., Rex, R., Lai, A., … Randles, A. (2025). Microfluidic Digital Twin for Enhanced Single-Cell Analysis (Vol. 15903 LNCS, pp. 283–297). https://doi.org/10.1007/978-3-031-97626-1_20

Jensen, C., Ghorbannia, A., Urick, D., Hughes, G. C., & Randles, A. (2025). A systematic quantification of hemodynamic differences persisting after aortic coarctation repair. Front Bioeng Biotechnol, 13, 1539256. https://doi.org/10.3389/fbioe.2025.1539256

Martin, A., Ladd, W., Wu, R., & Randles, A. (2025). Adaptive Physics Refinement for Anatomic Adhesive Dynamics Simulations (Vol. 15903 LNCS, pp. 268–282). https://doi.org/10.1007/978-3-031-97626-1_19

Martin, A., Liu, G., Joo, B., Wu, R., Kabir, M. S., Draeger, E. W., & Randles, A. (2024). Designing a GPU-Accelerated Communication Layer for Efficient Fluid-Structure Interaction Computations on Heterogeneous Systems. In International Conference for High Performance Computing Networking Storage and Analysis Sc. https://doi.org/10.1109/SC41406.2024.00099

Feiger, B., Jensen, C. W., Bryner, B. S., Segars, W. P., & Randles, A. (2024). Modeling the effect of patient size on cerebral perfusion during veno-arterial extracorporeal membrane oxygenation. Perfusion, 39(7), 1295–1303. https://doi.org/10.1177/02676591231187962

Tanade, C., Khan, N. S., Rakestraw, E., Ladd, W. D., Draeger, E. W., & Randles, A. (2024). Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins. NPJ Digital Medicine, 7(1), 236. https://doi.org/10.1038/s41746-024-01216-3

Chidyagwai, S. G., Kaplan, M. S., Jensen, C. W., Chen, J. S., Chamberlain, R. C., Hill, K. D., … Randles, A. (2024). Surgical Modulation of Pulmonary Artery Shear Stress: A Patient-Specific CFD Analysis of the Norwood Procedure. Cardiovasc Eng Technol, 15(4), 431–442. https://doi.org/10.1007/s13239-024-00724-3

Geddes, J., Randles, A., Tanade, C., Ladd, W., & Khan, N. S. (2024). Velocity Temporal Shape Affects Simulated Flow in Left Coronary Arteries (Accepted). Presented at the 24th International Conference on Computational Science, Malaga, Spain.

Vardhan, M., Tanade, C., Chen, S. J., Mahmood, O., Chakravartti, J., Jones, W. S., … Randles, A. (2024). Diagnostic Performance of Coronary Angiography Derived Computational Fractional Flow Reserve. J Am Heart Assoc, 13(13), e029941. https://doi.org/10.1161/JAHA.123.029941