Publications

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

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.

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

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

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

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

Tanade, C., Putney, S., & Randles, A. (2023). Establishing massively parallel models to examine the influence of cell heterogeneity on tumor growth. Journal of Computational Science, 71. https://doi.org/10.1016/j.jocs.2023.102059

Shi, H., Vardhan, M., & Randles, A. (2023). The Role of Immersion for Improving Extended Reality Analysis of Personalized Flow Simulations. Cardiovascular Engineering and Technology, 14(2), 194–203. https://doi.org/10.1007/s13239-022-00646-y

Pepona, M., Gounley, J., & Randles, A. (2023). Effect of constitutive law on the erythrocyte membrane response to large strains. Computers & Mathematics with Applications (Oxford, England : 1987), 132, 145–160. https://doi.org/10.1016/j.camwa.2022.12.009

Yousef, A., Draeger, E., & Randles, A. (2023). Low-Cost Post Hoc Reconstruction of HPC Simulations at Full Resolution. Presented at the The 13th IEEE Symposium on Large Data Analysis and Visualization, Melbourne, Australia: IEEE.

Ladd, W., Jensen, C., Vardhan, M., Ames, J., Hammond, J. R., Draeger, E. W., & Randles, A. (2023). Optimizing Cloud Computing Resource Usage for Hemodynamic Simulation. In Proceedings - 2023 IEEE International Parallel and Distributed Processing Symposium, IPDPS 2023 (pp. 568–578). https://doi.org/10.1109/IPDPS54959.2023.00063

Puleri, D. F., Martin, A. X., & Randles, A. (2022). Distributed Acceleration of Adhesive Dynamics Simulations. In Proceedings of 2022 29th European MPI Users’ Group Meeting (EuroMPI/USA’2022) : September 26-28, 2022, Chattanooga, TN. European MPI Users’ Group Meeting (29th : 2022 : Chattanooga, Tenn.) (Vol. 2022, pp. 37–45). https://doi.org/10.1145/3555819.3555832

Puleri, D. F., Roychowdhury, S., Balogh, P., Gounley, J., Draeger, E. W., Ames, J., … Randles, A. (2022). High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory. In Proceedings. IEEE International Conference on Cluster Computing (Vol. 2022, pp. 230–242). https://doi.org/10.1109/cluster51413.2022.00036

Puleri, D. F., & Randles, A. (2022). The role of adhesive receptor patterns on cell transport in complex microvessels. Biomechanics and Modeling in Mechanobiology, 21(4), 1079–1098. https://doi.org/10.1007/s10237-022-01575-4

Gounley, J., Vardhan, M., Draeger, E. W., Valero-Lara, P., Moore, S. V., & Randles, A. (2022). Propagation pattern for moment representation of the lattice Boltzmann method. IEEE Transactions on Parallel and Distributed Systems : A Publication of the IEEE Computer Society, 33(3), 642–653. https://doi.org/10.1109/tpds.2021.3098456