Publications
2025
Martin, A., Nezdyur, M., Tanade, C., & Randles, A. (2025). Establishing a massively parallel computational model of the adaptive immune response (Accepted). 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, 102570–102570. https://doi.org/10.1016/j.jocs.2025.102570
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
2024
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
Mavi, J. K., Tanade, C., Ladd, W., Geddes, J., Khan, N. S., & Randles, A. (2024). Hemodynamics comparison of an hour-long rest and activity state data in a human coronary digital twin. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference (Vol. 2024, pp. 1–4). https://doi.org/10.1109/embc53108.2024.10782436
Huber, M., Jiang, J., Tanade, C., & Randles, A. (2024). Identifying When Steady-State Flow Simulations In Patient-Specific Coronaries Recapitulate Pulsatile Flow Dynamics. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference (Vol. 2024, pp. 1–4). https://doi.org/10.1109/embc53108.2024.10781714
Ghorbannia, A., & Randles, A. (2024). Systematic characterization and automated alignment of coronary tree geometries. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference (Vol. 2024, pp. 1–4). https://doi.org/10.1109/embc53108.2024.10781665
Vemulapalli, S., Adebiyi, A., Jensen, C., Weissler, E. H., Inohara, T., Chen, S. J., … Randles, A. (2024). Leveraging Computational Fluid Dynamics for Next-Generation Preoperative Planning in Vascular Surgery. In Annu Int Conf IEEE Eng Med Biol Soc (Vol. 2024, pp. 1–4). United States. https://doi.org/10.1109/EMBC53108.2024.10781932
Wu, R., Kabir, M. S., Truskey, G. A., & Randles, A. (2024). Investigating the impact of sickle cell disease on red blood cell transport in complex capillary networks. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference (Vol. 2024, pp. 1–4). https://doi.org/10.1109/embc53108.2024.10781578
Tanade, C., & Randles, A. (n.d.). HarVI: Real-time intervention planning for coronary artery disease using machine learning (Accepted). Presented at the International Conference on Computational Science (ICCS), Malaga, Spain.
Seidel, E., Randles, A., Arthur, R., Bergman, K., Carlson, B., Deelman, E., … Reed, D. (2024). 2024 Advanced Scientific Computing Advisory Committee (ASCR) Facilities Subcommittee Recommendations. USDOE Office of Science (SC). https://doi.org/10.2172/2370379
Geddes, J. R., & Randles, A. (2024). Optimizing Temporal Waveform Analysis: A Novel Pipeline for Efficient Characterization of Left Coronary Artery Velocity Profiles. ArXiv.
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
2023
Nan, J., Roychowdhury, S., & Randles, A. (2023). Investigating the Influence of Heterogeneity Within Cell Types on Microvessel Network Transport. Cellular and Molecular Bioengineering, 16(5–6), 497–507. https://doi.org/10.1007/s12195-023-00790-y
Valero-Lara, P., Vetter, J., Gounley, J., & Randles, A. (2023). Moment Representation of Regularized Lattice Boltzmann Methods on NVIDIA and AMD GPUs. In ACM International Conference Proceeding Series (pp. 1697–1704). https://doi.org/10.1145/3624062.3624250
Yousef, A., & Randles, A. (2023). Enabling In Situ Visualization of Large-Scale Cellular Simulations. Presented at the ISAV23: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, Denver, CO.
Martin, A., Liu, G., Ladd, W., Lee, S., Gounley, J., Vetter, J., … Randles, A. (2023). Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations. In ACM International Conference Proceeding Series (pp. 1126–1137). https://doi.org/10.1145/3624062.3624188
Tanade, C., Rakestraw, E., Ladd, W., Draeger, E., & Randles, A. (2023). Cloud Computing to Enable Wearable-Driven Longitudinal Hemodynamic Maps. In International Conference for High Performance Computing, Networking, Storage and Analysis : [proceedings]. SC (Conference : Supercomputing) (Vol. 2023, p. 82). https://doi.org/10.1145/3581784.3607101
Roychowdhury, S., Balogh, P., Mahmud, S. T., Puleri, D. F., Martin, A., Gounley, J., … Randles, A. (2023). Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts. In International Conference for High Performance Computing, Networking, Storage and Analysis : [proceedings]. SC (Conference : Supercomputing) (Vol. 2023, p. 41). https://doi.org/10.1145/3581784.3607105
Randles, A., Draeger, E., & Yousef, A. (2023). Low-Cost Post Hoc Reconstruction of HPC Simulations at Full Resolution. 2023 IEEE 13th Symposium on Large Data Analysis and Visualization (LDAV), 17–21. https://doi.org/10.1109/LDAV60332.2023.00009
Roychowdhury, S., Draeger, E. W., & Randles, A. (2023). Establishing metrics to quantify spatial similarity in spherical and red blood cell distributions. Journal of Computational Science, 71. https://doi.org/10.1016/j.jocs.2023.102060