Publications

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

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 Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023. 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

Feiger, B., Jensen, C. W., Bryner, B. S., Segars, W. P., & Randles, A. (2023). Modeling the effect of patient size on cerebral perfusion during veno-arterial extracorporeal membrane oxygenation. Perfusion, 2676591231187962. https://doi.org/10.1177/02676591231187962

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

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

2022

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., 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., & 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

Chidyagwai, S. G., Vardhan, M., Kaplan, M., Chamberlain, R., Barker, P., & Randles, A. (2022). Characterization of hemodynamics in anomalous aortic origin of coronary arteries using patient-specific modeling. J Biomech, 132, 110919. https://doi.org/10.1016/j.jbiomech.2021.110919

Vardhan, M., Shi, H., Urick, D., Patel, M., Leopold, J. A., & Randles, A. (2022). The role of extended reality for planning coronary artery bypass graft surgery. In Proceedings - 2022 IEEE Visualization Conference - Short Papers, VIS 2022 (pp. 115–119). https://doi.org/10.1109/VIS54862.2022.00032

Feiger, B., Lorenzana-Saldivar, E., Cooke, C., Horstmeyer, R., Bishawi, M., Doberne, J., … Randles, A. (2022). Evaluation of U-Net Based Architectures for Automatic Aortic Dissection Segmentation. ACM Transactions on Computing for Healthcare, 3(1). https://doi.org/10.1145/3472302

Bishawi, M., Kaplan, M., Chidyagwai, S., Cappiello, J., Cherry, A., MacLeod, D., … Randles, A. (2022). Patient- and Ventilator-Specific Modeling to Drive the Use and Development of 3D Printed Devices for Rapid Ventilator Splitting During the COVID-19 Pandemic. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13352 LNCS, pp. 137–149). https://doi.org/10.1007/978-3-031-08757-8_13

Tanade, C., Putney, S., & Randles, A. (2022). Developing a Scalable Cellular Automaton Model of 3D Tumor Growth. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13350 LNCS, pp. 3–16). https://doi.org/10.1007/978-3-031-08751-6_1

Tanade, C., Chen, S. J., Leopold, J. A., & Randles, A. (2022). Analysis identifying minimal governing parameters for clinically accurate in silico fractional flow reserve. Frontiers in Medical Technology, 4, 1034801. https://doi.org/10.3389/fmedt.2022.1034801

Roychowdhury, S., Mahmud, S. T., Puleri, D. F., Lai, A., Rex, R., Li, B., … Randles, A. (2022). DEVELOPING A DIGITAL TWIN FOR SINGLE-CELL MECHANICAL PHENOTYPING MICROFLUIDIC DEVICES. In MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences (pp. 831–832).

Roychowdhury, S., Draeger, E. W., & Randles, A. (2022). Establishing Metrics to Quantify Underlying Structure in Vascular Red Blood Cell Distributions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13350 LNCS, pp. 89–102). https://doi.org/10.1007/978-3-031-08751-6_7

2021

Bazarin, R. L. M., Philippi, P. C., Randles, A., & Hegele, L. A. (2021). Moments-based method for boundary conditions in the lattice Boltzmann framework: A comparative analysis for the lid driven cavity flow. Computers and Fluids, 230. https://doi.org/10.1016/j.compfluid.2021.105142

Liu, X., Vardhan, M., Wen, Q., Das, A., Randles, A., & Chi, E. C. (2021). An Interpretable Machine Learning Model to Classify Coronary Bifurcation Lesions. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2021, 4432–4435. https://doi.org/10.1109/embc46164.2021.9631082