Publications

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, 17(4), 425–438. https://doi.org/10.1007/s13239-026-00836-y

Randles, A. (2026). Physiological Assessment of Coronary Artery Disease. The New England Journal of Medicine, 395(1), 80–83. https://doi.org/10.1056/nejme2602134

Yousef, A., Martin, A., & Randles, A. (2026). GPU Halo Replay: Lossless Twin Simulations for Flexible In Situ Analysis of Stencil-Based Solvers. In Pasc 2026 Platform for Advanced Scientific Computing Conference. https://doi.org/10.1145/3815572.3815746

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, 17(3), 300–316. https://doi.org/10.1007/s13239-026-00825-1

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

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

Deelman, E., Dongarra, J., Hendrickson, B., Randles, A., Reed, D., Seidel, E., & Yelick, K. (2026). Retrospective on the Lax Report: Then and Now. Computing in Science and Engineering, 28(2), 49–58. https://doi.org/10.1109/MCSE.2025.3647733

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

Yousef, A., Wetterer-Nelson, C., Han, M., Mateevitsi, V., Insley, J., Rizzi, S., … Randles, A. (2026). Instrumenting Lightweight, Modular Machine Learning Training and Inference in Parallel Solvers. In Lecture Notes in Computer Science (Vol. 16784 LNCS, pp. 123–137). https://doi.org/10.1007/978-3-032-29924-6_9

Martin, A., Kabir, M. S., Wu, R., & Randles, A. (2026). Multiscale Modeling of Shear-Dependent Tumor Cell Adhesion (Vol. 16783 LNCS, pp. 442–456). https://doi.org/10.1007/978-3-032-29921-5_30

Wu, R., Kabir, M. S., Martin, A., Ma, W., & Randles, A. (2026). Investigating the Influence of Red Blood Cell Heterogeneity on Cell Transport and Blood Flow Hemodynamics (Vol. 16789 LNCS, pp. 213–227). https://doi.org/10.1007/978-3-032-29918-5_15

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. The 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 (Woodbury, N.Y. : 1994), 37(9), 091926. 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

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

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

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