Journal articles or Book chapters PUBLISHED

1. Saxena, Y; Riley, L; Wu, R; Kabir, MS; Randles, A; Segura, T, 3D pore shape is predictable in randomly packed particle systems., Matter (October, 2025), pp. 102493 [doi]  [abs].
2. Mac Grory, B; Randles, A; Urick, DM; Schwartz, FR; Hasan, D; Calabrese, ED, Photon-Counting Computed Tomography for Evaluation of Coiled Intracranial Aneurysms., AJNR Am J Neuroradiol (September, 2025), pp. ajnr.A9015 [doi]  [abs].
3. Ghorbannia, A; Tanade, C; Yousef, A; Khan, NS; Vardhan, M; Chi, JT; Roychowdhury, S; Das, A; Leopold, JA; Chi, EC; Randles, A, Simulation-based machine learning for real-time assessment of side-branch hemodynamics in coronary bifurcation lesions, International Journal of High Performance Computing Applications, vol. 39 no. 5 (September, 2025), pp. 678-691, SAGE Publications [doi]  [abs].
4. Khan, NS; Tanade, C; Geddes, J; Randles, A, Establishing hemodynamic convergence framework for coronary digital twins under realistic dynamic heart rates, Physics of Fluids, vol. 37 no. 9 (September, 2025), AIP Publishing [doi]  [abs].
5. Geddes, JR; Jensen, CW; Tanade, C; Ghorbannia, A; Fudim, M; Patel, MR; Randles, A, Digital twins for noninvasively measuring predictive markers of right heart failure., NPJ Digit Med, vol. 8 no. 1 (August, 2025), pp. 545 [doi]  [abs].
6. Aran, K; Li, J; Randles, A; Wan, Y, Meet the winners of the 2024 Sony Women in Technology Award, Nature Reviews Electrical Engineering, vol. 2 no. 5 (May, 2025), pp. 297-301, Springer Science and Business Media LLC [doi] .
7. Martin, A; Nezdyur, M; Tanade, C; Randles, A, Establishing a massively parallel computational model of the adaptive immune response, Journal of Computational Science, vol. 87 (May, 2025), pp. 102555-102555, Elsevier BV [doi]  [abs].
8. Tanade, C; Randles, A, Real-time virtual intervention for simple and serial coronary artery disease using the HarVI framework, Journal of Computational Science, vol. 87 (May, 2025), pp. 102570-102570, Elsevier BV [doi]  [abs].
9. Geddes, JR; King, TD; Tanade, C; Ladd, W; Khan, NS; Randles, A, Impact of inlet velocity waveform shape on hemodynamics, Journal of Computational Science, vol. 87 (May, 2025) [doi]  [abs].
10. Deelman, E; Dongarra, J; Hendrickson, B; Randles, A; Reed, D; Seidel, E; Yelick, K, High-performance computing at a crossroads., Science (New York, N.Y.), vol. 387 no. 6736 (February, 2025), pp. 829-831 [doi]  [abs].
11. Jensen, C; Ghorbannia, A; Urick, D; Hughes, GC; Randles, A, A systematic quantification of hemodynamic differences persisting after aortic coarctation repair., Front Bioeng Biotechnol, vol. 13 (2025), pp. 1539256, Frontiers Media S.A. [doi]  [abs].
12. Feiger, B; Jensen, CW; Bryner, BS; Segars, WP; Randles, A, Modeling the effect of patient size on cerebral perfusion during veno-arterial extracorporeal membrane oxygenation., Perfusion, vol. 39 no. 7 (October, 2024), pp. 1295-1303 [doi]  [abs].
13. Tanade, C; Khan, NS; Rakestraw, E; Ladd, WD; Draeger, EW; Randles, A, Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins., NPJ digital medicine, vol. 7 no. 1 (September, 2024), pp. 236, Springer Science and Business Media LLC [doi]  [abs].
14. Chidyagwai, SG; Kaplan, MS; Jensen, CW; Chen, JS; Chamberlain, RC; Hill, KD; Barker, PCA; Slesnick, TC; Randles, A, Surgical Modulation of Pulmonary Artery Shear Stress: A Patient-Specific CFD Analysis of the Norwood Procedure., Cardiovasc Eng Technol, vol. 15 no. 4 (August, 2024), pp. 431-442 [doi]  [abs].
15. Vardhan, M; Tanade, C; Chen, SJ; Mahmood, O; Chakravartti, J; Jones, WS; Kahn, AM; Vemulapalli, S; Patel, M; Leopold, JA; Randles, A, Diagnostic Performance of Coronary Angiography Derived Computational Fractional Flow Reserve., J Am Heart Assoc, vol. 13 no. 13 (July, 2024), pp. e029941 [doi]  [abs].
16. Tanade, C; Felice, N; Samei, E; Randles, A; Segars, WP, Enhanced CT simulation using realistic vascular flow dynamics, Medical Imaging 2024 - Physics of Medical Imaging, vol. 12925 (April, 2024), pp. 399-404, SPIE [doi] .
17. Geddes, JR; Randles, A, Optimizing Temporal Waveform Analysis: A Novel Pipeline for Efficient Characterization of Left Coronary Artery Velocity Profiles., ArXiv (February, 2024)  [abs].
18. Taufer, M; Hoefler, T; Hammond, J; Randles, A, Proceedings of ISC-High Performance 2024, Research Paper Proceedings of the Isc High Performance 2024 (January, 2024) .
19. Nan, J; Roychowdhury, S; Randles, A, Investigating the Influence of Heterogeneity Within Cell Types on Microvessel Network Transport., Cellular and molecular bioengineering, vol. 16 no. 5-6 (December, 2023), pp. 497-507 [doi]  [abs].
20. Randles, A; Draeger, E; Yousef, A, Low-Cost Post Hoc Reconstruction of HPC Simulations at Full Resolution, 2023 IEEE 13th Symposium on Large Data Analysis and Visualization (LDAV) (October, 2023), pp. 17-21, IEEE [doi] .
21. Roychowdhury, S; Draeger, EW; Randles, A, Establishing metrics to quantify spatial similarity in spherical and red blood cell distributions, Journal of Computational Science, vol. 71 (July, 2023) [doi]  [abs].
22. Tanade, C; Putney, S; Randles, A, Establishing massively parallel models to examine the influence of cell heterogeneity on tumor growth, Journal of Computational Science, vol. 71 (July, 2023) [doi]  [abs].
23. Shi, H; Vardhan, M; Randles, A, The Role of Immersion for Improving Extended Reality Analysis of Personalized Flow Simulations., Cardiovascular engineering and technology, vol. 14 no. 2 (April, 2023), pp. 194-203 [doi]  [abs].
24. Pepona, M; Gounley, J; Randles, A, Effect of constitutive law on the erythrocyte membrane response to large strains., Computers & mathematics with applications (Oxford, England : 1987), vol. 132 (February, 2023), pp. 145-160 [doi]  [abs].
25. Puleri, DF; Randles, A, The role of adhesive receptor patterns on cell transport in complex microvessels., Biomechanics and modeling in mechanobiology, vol. 21 no. 4 (August, 2022), pp. 1079-1098 [doi]  [abs].
26. Gounley, J; Vardhan, M; Draeger, EW; Valero-Lara, P; Moore, SV; Randles, A, Propagation pattern for moment representation of the lattice Boltzmann method., IEEE transactions on parallel and distributed systems : a publication of the IEEE Computer Society, vol. 33 no. 3 (March, 2022), pp. 642-653 [doi]  [abs].
27. Chidyagwai, SG; Vardhan, M; Kaplan, M; Chamberlain, R; Barker, P; Randles, A, Characterization of hemodynamics in anomalous aortic origin of coronary arteries using patient-specific modeling., J Biomech, vol. 132 (February, 2022), pp. 110919 [doi]  [abs].
28. Feiger, B; Lorenzana-Saldivar, E; Cooke, C; Horstmeyer, R; Bishawi, M; Doberne, J; Hughes, GC; Ranney, D; Voigt, S; Randles, A, Evaluation of U-Net Based Architectures for Automatic Aortic Dissection Segmentation, ACM Transactions on Computing for Healthcare, vol. 3 no. 1 (January, 2022) [doi]  [abs].
29. Tanade, C; Chen, SJ; Leopold, JA; Randles, A, Analysis identifying minimal governing parameters for clinically accurate in silico fractional flow reserve., Frontiers in medical technology, vol. 4 (January, 2022), pp. 1034801 [doi]  [abs].
30. Vardhan, M; Gounley, J; Chen, SJ; Nair, P; Wei, W; Hegele, L; Kusner, J; Kahn, AM; Frakes, D; Leopold, JA; Randles, A, Evaluation of intracoronary hemodynamics identifies perturbations in vorticity, Frontiers in Systems Biology, vol. 2 (January, 2022) [doi]  [abs].
31. Bazarin, RLM; Philippi, PC; Randles, A; Hegele, LA, Moments-based method for boundary conditions in the lattice Boltzmann framework: A comparative analysis for the lid driven cavity flow, Computers and Fluids, vol. 230 (November, 2021) [doi]  [abs].
32. Liu, X; Vardhan, M; Wen, Q; Das, A; Randles, A; Chi, EC, 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, vol. 2021 (November, 2021), pp. 4432-4435 [doi]  [abs].
33. Tanade, C; Feiger, B; Vardhan, M; Chen, SJ; Leopold, JA; Randles, A, Global Sensitivity Analysis For Clinically Validated 1D Models of Fractional Flow Reserve., Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2021 (November, 2021), pp. 4395-4398 [doi]  [abs].
34. Herschlag, G; Lee, S; Vetter, JS; Randles, A, Analysis of GPU Data Access Patterns on Complex Geometries for the D3Q19 Lattice Boltzmann Algorithm, IEEE Transactions on Parallel and Distributed Systems, vol. 32 no. 10 (October, 2021), pp. 2400-2414 [doi]  [abs].
35. Puleri, DF; Balogh, P; Randles, A, Computational models of cancer cell transport through the microcirculation., Biomechanics and modeling in mechanobiology, vol. 20 no. 4 (August, 2021), pp. 1209-1230 [doi]  [abs].
36. Balogh, P; Gounley, J; Roychowdhury, S; Randles, A, A data-driven approach to modeling cancer cell mechanics during microcirculatory transport., Scientific reports, vol. 11 no. 1 (July, 2021), pp. 15232 [doi]  [abs].
37. Randles, A; Wirsching, H-G; Dean, JA; Cheng, Y-K; Emerson, S; Pattwell, SS; Holland, EC; Michor, F, Computational modelling of perivascular-niche dynamics for the optimization of treatment schedules for glioblastoma., Nature biomedical engineering, vol. 5 no. 4 (April, 2021), pp. 346-359 [doi]  [abs].
38. Vardhan, M; Gounley, J; Chen, SJ; Chi, EC; Kahn, AM; Leopold, JA; Randles, A, Non-invasive characterization of complex coronary lesions., Scientific reports, vol. 11 no. 1 (April, 2021), pp. 8145 [doi]  [abs].
39. Vardhan, M; Randles, A, Application of physics-based flow models in cardiovascular medicine: Current practices and challenges., Biophysics reviews, vol. 2 no. 1 (March, 2021), pp. 011302 [doi]  [abs].
40. Feiger, B; Adebiyi, A; Randles, A, Multiscale modeling of blood flow to assess neurological complications in patients supported by venoarterial extracorporeal membrane oxygenation., Computers in biology and medicine, vol. 129 (February, 2021), pp. 104155 [doi]  [abs].
41. Bardhan, J; Leung, MA; Martin, E; Randles, A, DOE Computational Science Graduate Fellowship Research Showcase, Computing in Science and Engineering, vol. 23 no. 6 (January, 2021), pp. 5-8 [doi] .
42. Kaplan, M; Kneifel, C; Orlikowski, V; Dorff, J; Newton, M; Howard, A; Shinn, D; Bishawi, M; Chidyagwai, S; Balogh, P; Randles, A, Cloud Computing for COVID-19: Lessons Learned From Massively Parallel Models of Ventilator Splitting., Computing in science & engineering, vol. 22 no. 6 (November, 2020), pp. 37-47 [doi]  [abs].
43. Pepona, M; Balogh, P; Puleri, DF; Hynes, WF; Robertson, C; Dubbin, K; Alvarado, J; Moya, ML; Randles, A, Investigating the Interaction Between Circulating Tumor Cells and Local Hydrodynamics via Experiment and Simulations., Cellular and molecular bioengineering, vol. 13 no. 5 (October, 2020), pp. 527-540 [doi]  [abs].
44. Jang, LK; Alvarado, JA; Pepona, M; Wasson, EM; Nash, LD; Ortega, JM; Randles, A; Maitland, DJ; Moya, ML; Hynes, WF, Three-dimensional bioprinting of aneurysm-bearing tissue structure for endovascular deployment of embolization coils., Biofabrication, vol. 13 no. 1 (October, 2020) [doi]  [abs].
45. Bishawi, M; Kaplan, M; Chidyagwai, S; Cappiello, J; Cherry, A; MacLeod, D; Gall, K; Evans, N; Kim, M; Shaha, R; Whittle, J; Hollidge, M; Truskey, G; Randles, A, Rapid Ventilator Splitting During COVID-19 Pandemic Using 3D Printed Devices and Numerical Modeling of 200 Million Patient Specific Air Flow Scenarios., Res Sq (August, 2020) [doi]  [abs].
46. Hynes, WF; Pepona, M; Robertson, C; Alvarado, J; Dubbin, K; Triplett, M; Adorno, JJ; Randles, A; Moya, ML, Examining metastatic behavior within 3D bioprinted vasculature for the validation of a 3D computational flow model., Science advances, vol. 6 no. 35 (August, 2020), pp. eabb3308 [doi]  [abs].
47. Cherian, J; Dabagh, M; Srinivasan, VM; Chen, S; Johnson, J; Wakhloo, A; Gupta, V; Macho, J; Randles, A; Kan, P, Balloon-Mounted Stents for Treatment of Refractory Flow Diverting Device Wall Malapposition., Operative neurosurgery (Hagerstown, Md.), vol. 19 no. 1 (July, 2020), pp. 37-42 [doi]  [abs].
48. Ames, J; Puleri, DF; Balogh, P; Gounley, J; Draeger, EW; Randles, A, Multi-GPU Immersed Boundary Method Hemodynamics Simulations., Journal of computational science, vol. 44 (July, 2020), pp. 101153 [doi]  [abs].
49. Feiger, B; Gounley, J; Adler, D; Leopold, JA; Draeger, EW; Chaudhury, R; Ryan, J; Pathangey, G; Winarta, K; Frakes, D; Michor, F; Randles, A, Accelerating massively parallel hemodynamic models of coarctation of the aorta using neural networks., Scientific reports, vol. 10 no. 1 (June, 2020), pp. 9508 [doi]  [abs].
50. Feiger, B; Kochar, A; Gounley, J; Bonadonna, D; Daneshmand, M; Randles, A, Determining the impacts of venoarterial extracorporeal membrane oxygenation on cerebral oxygenation using a one-dimensional blood flow simulator., Journal of biomechanics, vol. 104 (May, 2020), pp. 109707 [doi]  [abs].
51. Shi, H; Ames, J; Randles, A, Harvis: an interactive virtual reality tool for hemodynamic modification and simulation, Journal of Computational Science, vol. 43 (May, 2020) [doi]  [abs].
52. Dabagh, M; Gounley, J; Randles, A, Localization of Rolling and Firm-Adhesive Interactions Between Circulating Tumor Cells and the Microvasculature Wall., Cellular and molecular bioengineering, vol. 13 no. 2 (April, 2020), pp. 141-154 [doi]  [abs].
53. Chen, K; Breitner, S; Wolf, K; Rai, M; Meisinger, C; Heier, M; Kuch, B; Peters, A; Schneider, A, Projection of Temperature-Related Myocardial Infarction in Augsburg, Germany: Moving on From the Paris Agreement on Climate Change., Deutsches Arzteblatt international, vol. 116 no. 31-32 (August, 2019), pp. 521-527 [doi]  [abs].
54. Lee, S; Gounley, J; Randles, A; Vetter, JS, Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures, Journal of Parallel and Distributed Computing, vol. 129 (July, 2019), pp. 1-13 [doi]  [abs].
55. Dabagh, M; Nair, P; Gounley, J; Frakes, D; Gonzalez, LF; Randles, A, Hemodynamic and morphological characteristics of a growing cerebral aneurysm., Neurosurg Focus, vol. 47 no. 1 (July, 2019), pp. E13 [doi]  [abs].
56. Feiger, B; Vardhan, M; Gounley, J; Mortensen, M; Nair, P; Chaudhury, R; Frakes, D; Randles, A, Suitability of lattice Boltzmann inlet and outlet boundary conditions for simulating flow in image-derived vasculature., International journal for numerical methods in biomedical engineering, vol. 35 no. 6 (June, 2019), pp. e3198 [doi]  [abs].
57. Vardhan, M; Gounley, J; Chen, SJ; Kahn, AM; Leopold, JA; Randles, A, The importance of side branches in modeling 3D hemodynamics from angiograms for patients with coronary artery disease., Scientific reports, vol. 9 no. 1 (June, 2019), pp. 8854 [doi]  [abs].
58. Grigoryan, B; Paulsen, SJ; Corbett, DC; Sazer, DW; Fortin, CL; Zaita, AJ; Greenfield, PT; Calafat, NJ; Gounley, JP; Ta, AH; Johansson, F; Randles, A; Rosenkrantz, JE; Louis-Rosenberg, JD; Galie, PA; Stevens, KR; Miller, JS, Multivascular networks and functional intravascular topologies within biocompatible hydrogels., Science (New York, N.Y.), vol. 364 no. 6439 (May, 2019), pp. 458-464 [doi]  [abs].
59. Chen, K; Breitner, S; Wolf, K; Hampel, R; Meisinger, C; Heier, M; von Scheidt, W; Kuch, B; Peters, A; Schneider, A; KORA Study Group, Temporal variations in the triggering of myocardial infarction by air temperature in Augsburg, Germany, 1987-2014., European heart journal, vol. 40 no. 20 (May, 2019), pp. 1600-1608 [doi]  [abs].
60. Gounley, J; Vardhan, M; Randles, A, A Framework for Comparing Vascular Hemodynamics at Different Points in Time., Computer physics communications, vol. 235 (February, 2019), pp. 1-8 [doi]  [abs].
61. Gounley, J; Draeger, EW; Oppelstrup, T; Krauss, WD; Gunnels, JA; Chaudhury, R; Nair, P; Frakes, D; Leopold, JA; Randles, A, Computing the ankle-brachial index with parallel computational fluid dynamics., Journal of biomechanics, vol. 82 (January, 2019), pp. 28-37 [doi]  [abs].
62. Dabagh, M; Randles, A, Role of deformable cancer cells on wall shear stress-associated-VEGF secretion by endothelium in microvasculature., PloS one, vol. 14 no. 2 (January, 2019), pp. e0211418 [doi]  [abs].
63. Hegele, LA; Scagliarini, A; Sbragaglia, M; Mattila, KK; Philippi, PC; Puleri, DF; Gounley, J; Randles, A, High-Reynolds-number turbulent cavity flow using the lattice Boltzmann method, Physical Review E, vol. 98 no. 4 (October, 2018), American Physical Society (APS) [doi]  [abs].
64. Rafat, M; Stone, HA; Auguste, DT; Dabagh, M; Randles, A; Heller, M; Rabinov, JD, Impact of diversity of morphological characteristics and Reynolds number on local hemodynamics in basilar aneurysms, Aiche Journal, vol. 64 no. 7 (July, 2018), pp. 2792-2802, WILEY [doi]  [abs].
65. Randles, A; Frakes, DH; Leopold, JA, Computational Fluid Dynamics and Additive Manufacturing to Diagnose and Treat Cardiovascular Disease., Trends in biotechnology, vol. 35 no. 11 (November, 2017), pp. 1049-1061 [doi]  [abs].
66. Dabagh, M; Jalali, P; Butler, PJ; Randles, A; Tarbell, JM, Mechanotransmission in endothelial cells subjected to oscillatory and multi-directional shear flow., Journal of the Royal Society, Interface, vol. 14 no. 130 (May, 2017), pp. 20170185 [doi]  [abs].
67. Randles, A; Draeger, EW; Bailey, PE, Massively parallel simulations of hemodynamics in the primary large arteries of the human vasculature., Journal of computational science, vol. 9 (July, 2015), pp. 70-75, Elsevier BV [doi]  [abs].
68. Whitley, HD; Scullard, CR; Benedict, LX; Castor, JI; Randles, A; Glosli, JN; Richards, DF; Desjarlais, MP; Graziani, FR, Lenard-Balescu calculations and classical molecular dynamics simulations of electrical and thermal conductivities of hydrogen plasmas, Contributions to Plasma Physics, vol. 55 no. 2-3 (February, 2015), pp. 192-202, WILEY [doi]  [abs].
69. You, Y; Fu, H; Song, SL; Randles, A; Kerbyson, D; Marquez, A; Yang, G; Hoisie, A, Scaling Support Vector Machines on modern HPC platforms, Journal of Parallel and Distributed Computing, vol. 76 (January, 2015), pp. 16-31, Elsevier BV [doi]  [abs].
70. Randles, A; Kaxiras, E, Parallel in time approximation of the lattice Boltzmann method for laminar flows, Journal of Computational Physics, vol. 270 (August, 2014), pp. 577-586, Elsevier BV [doi]  [abs].
71. Almendro, V; Cheng, Y-K; Randles, A; Itzkovitz, S; Marusyk, A; Ametller, E; Gonzalez-Farre, X; Muñoz, M; Russnes, HG; Helland, A; Rye, IH; Borresen-Dale, A-L; Maruyama, R; van Oudenaarden, A; Dowsett, M; Jones, RL; Reis-Filho, J; Gascon, P; Gönen, M; Michor, F; Polyak, K, Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity., Cell reports, vol. 6 no. 3 (February, 2014), pp. 514-527 [doi]  [abs].
72. Randles, A; Draeger, E; Michor, F, Analysis of pressure gradient across aortic stenosis with massively parallel computational simulations, Computing in Cardiology, vol. 41 no. January (January, 2014), pp. 217-220  [abs].
73. Randles, A; Kaxiras, E, A spatio-temporal coupling method to reduce the time-to-solution of cardiovascular simulations, Proceedings of the International Parallel and Distributed Processing Symposium IPDPS (January, 2014), pp. 593-602 [doi]  [abs].
74. Keyes, DE; McInnes, LC; Woodward, C; Gropp, W; Myra, E; Pernice, M; Bell, J; Brown, J; Clo, A; Connors, J; Constantinescu, E; Estep, D; Evans, K; Farhat, C; Hakim, A; Hammond, G; Hansen, G; Hill, J; Isaac, T; Jiao, X; Jordan, K; Kaushik, D; Kaxiras, E; Koniges, A; Lee, K; Lott, A; Lu, Q; Magerlein, J; Maxwell, R; McCourt, M; Mehl, M; Pawlowski, R; Randles, AP; Reynolds, D; Rivière, B; Rüde, U; Scheibe, T; Shadid, J; Sheehan, B; Shephard, M; Siegel, A; Smith, B; Tang, X; Wilson, C; Wohlmuth, B, Multiphysics simulations: Challenges and opportunities, International Journal of High Performance Computing Applications, vol. 27 no. 1 (February, 2013), pp. 4-83, SAGE Publications [doi]  [abs].
75. Randles, AP, Massively parallel model of evolutionary game dynamics, Proceedings 2012 Sc Companion High Performance Computing Networking Storage and Analysis Scc 2012 (December, 2012), pp. 1531, IEEE [doi]  [abs].
76. Randles, A; Baecher, M; Pfister, H; Kaxiras, EK, A Lattice Boltzmann Simulation of Hemodynamics in a Patient-Speci c Aortic Coarctation Model, edited by Camara, O; Pop, M; Mansi, T; Sermesant, M; Young, A, Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges:, vol. 7746 (October, 2012), pp. 17-25, Springer Berlin Heidelberg [978-3-642-36961-2_3], [doi]  [abs].
77. Borkin, MA; Gajos, KZ; Peters, A; Mitsouras, D; Melchionna, S; Rybicki, FJ; Feldman, CL; Pfister, H, Evaluation of artery visualizations for heart disease diagnosis., IEEE transactions on visualization and computer graphics, vol. 17 no. 12 (December, 2011), pp. 2479-2488 [doi]  [abs].
78. Robson, B; Li, J; Dettinger, R; Peters, A; Boyer, SK, Drug discovery using very large numbers of patents: general strategy with extensive use of match and edit operations., Journal of computer-aided molecular design, vol. 25 no. 5 (May, 2011), pp. 427-441, Springer Science and Business Media LLC [doi]  [abs].
79. Jiang, K; Thorsen, O; Peters, A; Smith, B; Sosa, CP, An Efficient Parallel Implementation of the Hidden Markov Methods for Genomic Sequence-Search on a Massively Parallel System, IEEE Transactions on Parallel and Distributed Systems, vol. 19 no. 1 (January, 2008), pp. 15-23, Institute of Electrical and Electronics Engineers (IEEE) [doi] .
80. Pang, Y-P; Mullins, TJ; Swartz, BA; McAllister, JS; Smith, BE; Archer, CJ; Musselman, RG; Peters, AE; Wallenfelt, BP; Pinnow, KW, EUDOC on the IBM Blue Gene/L system: Accelerating the transfer of drug discoveries from laboratory to patient, IBM Journal of Research and Development, vol. 52 no. 1.2 (January, 2008), pp. 69-81, IBM [doi] .

Books

1. Vardhan, M; Shi, H; Gounley, J; Chen, SJ; Kahn, A; Leopold, J; Randles, A, Correction to: Investigating the Role of VR in a Simulation-Based Medical Planning System for Coronary Interventions (Medical Image Computing and Computer Assisted Intervention – MICCAI 2019, LNCS 11768, 10.1007/978-3-030-32254-0_41), vol. 11768 LNCS (January, 2019), pp. C1 [doi]  [abs].

Papers Published

1. Martin, A; Yousef, A; Liu, G; Ladd, W; Georgiadou, A; Stoop, J; Randles, A, Performance Portability Evaluation of Fluid-Structure Interaction Simulations on Heterogeneous Platforms, https://ieeexplore.ieee.org/xpl/conhome/11008903/proceeding (May, 2025), pp. 1-11, IEEE .
2. Geddes, J; Randles, A; Tanade, C; Ladd, W; Khan, NS, Velocity Temporal Shape Affects Simulated Flow in Left Coronary Arteries (July, 2024) .
3. Mavi, JK; Tanade, C; Ladd, W; Geddes, J; Khan, NS; Randles, A, Hemodynamics comparison of an hour-long rest and activity state data in a human coronary digital twin., Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2024 (July, 2024), pp. 1-4 [doi]  [abs].
4. Ghorbannia, A; Randles, A, Systematic characterization and automated alignment of coronary tree geometries., Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2024 (July, 2024), pp. 1-4 [doi]  [abs].
5. Vemulapalli, S; Adebiyi, A; Jensen, C; Weissler, EH; Inohara, T; Chen, SJ; Rakestraw, E; Southerland, K; Randles, A, Leveraging Computational Fluid Dynamics for Next-Generation Preoperative Planning in Vascular Surgery., Annu Int Conf IEEE Eng Med Biol Soc, vol. 2024 (July, 2024), pp. 1-4 [doi]  [abs].
6. Huber, M; Jiang, J; Tanade, C; Randles, A, Identifying When Steady-State Flow Simulations In Patient-Specific Coronaries Recapitulate Pulsatile Flow Dynamics., Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2024 (July, 2024), pp. 1-4 [doi]  [abs].
7. Wu, R; Kabir, MS; Truskey, GA; Randles, A, Investigating the impact of sickle cell disease on red blood cell transport in complex capillary networks., Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2024 (July, 2024), pp. 1-4 [doi]  [abs].
8. Seidel, E; Randles, A; Arthur, R; Bergman, K; Carlson, B; Deelman, E; Grout, R; Hendrickson, B; Reed, D, 2024 Advanced Scientific Computing Advisory Committee (ASCR) Facilities Subcommittee Recommendations (May, 2024), USDOE Office of Science (SC) [doi] .
9. Martin, A; Liu, G; Joo, B; Wu, R; Kabir, MS; Draeger, EW; Randles, A, Designing a GPU-Accelerated Communication Layer for Efficient Fluid-Structure Interaction Computations on Heterogeneous Systems, International Conference for High Performance Computing Networking Storage and Analysis Sc (January, 2024) [doi]  [abs].
10. Yousef, A; Randles, A, Enabling In Situ Visualization of Large-Scale Cellular Simulations (November, 2023) .
11. Martin, A; Liu, G; Ladd, W; Lee, S; Gounley, J; Vetter, J; Patel, S; Rizzi, S; Mateevitsi, V; Insley, J; Randles, A, Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations, ACM International Conference Proceeding Series (November, 2023), pp. 1126-1137, ACM [doi]  [abs].
12. Valero-Lara, P; Vetter, J; Gounley, J; Randles, A, Moment Representation of Regularized Lattice Boltzmann Methods on NVIDIA and AMD GPUs, ACM International Conference Proceeding Series (November, 2023), pp. 1697-1704, ACM [doi]  [abs].
13. Tanade, C; Rakestraw, E; Ladd, W; Draeger, E; Randles, A, Cloud Computing to Enable Wearable-Driven Longitudinal Hemodynamic Maps., International Conference for High Performance Computing, Networking, Storage and Analysis : [proceedings]. SC (Conference : Supercomputing), vol. 2023 (November, 2023), pp. 82, ACM [doi]  [abs].
14. Roychowdhury, S; Balogh, P; Mahmud, ST; Puleri, DF; Martin, A; Gounley, J; Draeger, EW; Randles, A, Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts., International Conference for High Performance Computing, Networking, Storage and Analysis : [proceedings]. SC (Conference : Supercomputing), vol. 2023 (November, 2023), pp. 41, ACM [doi]  [abs].
15. Yousef, A; Draeger, E; Randles, A, Low-Cost Post Hoc Reconstruction of HPC Simulations at Full Resolution (January, 2023), IEEE .
16. Ladd, W; Jensen, C; Vardhan, M; Ames, J; Hammond, JR; Draeger, EW; Randles, A, Optimizing Cloud Computing Resource Usage for Hemodynamic Simulation, Proceedings 2023 IEEE International Parallel and Distributed Processing Symposium IPDPS 2023 (January, 2023), pp. 568-578 [doi]  [abs].
17. Puleri, DF; Martin, AX; Randles, A, Distributed Acceleration of Adhesive Dynamics Simulations., 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 (September, 2022), pp. 37-45 [doi]  [abs].
18. Puleri, DF; Roychowdhury, S; Balogh, P; Gounley, J; Draeger, EW; Ames, J; Adebiyi, A; Chidyagwai, S; Hernández, B; Lee, S; Moore, SV; Vetter, JS; Randles, A, High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory., Proceedings. IEEE International Conference on Cluster Computing, vol. 2022 (September, 2022), pp. 230-242 [doi]  [abs].
19. Bishawi, M; Kaplan, M; Chidyagwai, S; Cappiello, J; Cherry, A; MacLeod, D; Gall, K; Evans, N; Kim, M; Shaha, R; Whittle, J; Hollidge, M; Truskey, G; Randles, A, Patient- and Ventilator-Specific Modeling to Drive the Use and Development of 3D Printed Devices for Rapid Ventilator Splitting During the COVID-19 Pandemic, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 13352 LNCS (January, 2022), pp. 137-149 [doi]  [abs].
20. Tanade, C; Putney, S; Randles, A, Developing a Scalable Cellular Automaton Model of 3D Tumor Growth, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 13350 LNCS (January, 2022), pp. 3-16 [doi]  [abs].
21. Roychowdhury, S; Draeger, EW; Randles, A, Establishing Metrics to Quantify Underlying Structure in Vascular Red Blood Cell Distributions, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 13350 LNCS (January, 2022), pp. 89-102 [doi]  [abs].
22. Vardhan, M; Shi, H; Urick, D; Patel, M; Leopold, JA; Randles, A, The role of extended reality for planning coronary artery bypass graft surgery, Proceedings 2022 IEEE Visualization Conference Short Papers Vis 2022 (January, 2022), pp. 115-119 [doi]  [abs].
23. Roychowdhury, S; Mahmud, ST; Puleri, DF; Lai, A; Rex, R; Li, B; Sohn, LL; Randles, A, DEVELOPING A DIGITAL TWIN FOR SINGLE-CELL MECHANICAL PHENOTYPING MICROFLUIDIC DEVICES, Microtas 2022 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences (January, 2022), pp. 831-832  [abs].
24. Feiger, B; Lorenzana, E; Ranney, D; Bishawi, M; Doberne, J; Vekstein, A; Voigt, S; Hughes, C; Randles, A, Predicting aneurysmal degeneration of type B aortic dissection with computational fluid dynamics, Proceedings of the 12th ACM Conference on Bioinformatics Computational Biology and Health Informatics Bcb 2021 (January, 2021) [doi]  [abs].
25. Puleri, DF; Roychowdhury, S; Ames, J; Randles, A, Computational Framework to Evaluate the Hydrodynamics of Cell Scaffold Geometries., Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2020 (July, 2020), pp. 2299-2302 [doi]  [abs].
26. Roychowdhury, S; Gounley, J; Randles, A, Evaluating the Influence of Hemorheological Parameters on Circulating Tumor Cell Trajectory and Simulation Time, Proceedings of the Platform for Advanced Scientific Computing Conference Pasc 2020 (June, 2020) [doi]  [abs].
27. Vardhan, M; Gounley, J; Hegele, L; Draeger, EW; Randles, A, Moment representation in the lattice Boltzmann method on massively parallel hardware, International Conference for High Performance Computing Networking Storage and Analysis Sc (November, 2019) [doi]  [abs].
28. Ames, J; Rizzi, S; Insley, J; Patel, S; Hernández, B; Draeger, EW; Randles, A, Low-Overhead in Situ Visualization Using Halo Replay, 2019 IEEE 9th Symposium on Large Data Analysis and Visualization Ldav 2019 (October, 2019), pp. 16-26 [doi]  [abs].
29. Herschlag, G; Gounley, J; Roychowdhury, S; Draeger, EW; Randles, A, Multi-physics simulations of particle tracking in arterial geometries with a scalable moving window algorithm, Proceedings IEEE International Conference on Cluster Computing Iccc, vol. 2019-September (September, 2019) [doi]  [abs].
30. Gounley, J; Draeger, EW; Randles, A, Immersed Boundary Method Halo Exchange in a Hemodynamics Application, Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, vol. 11536 LNCS (January, 2019), pp. 441-455 [doi]  [abs].
31. Herschlag, G; Lee, S; Vetter, JS; Randles, A, GPU data access on complex geometries for D3Q19 lattice boltzmann method, Proceedings 2018 IEEE 32nd International Parallel and Distributed Processing Symposium IPDPS 2018 (August, 2018), pp. 825-834, IEEE [doi]  [abs].
32. Vardhan, M; Das, A; Gouruev, J; Randles, A, Computational fluid modeling to understand the role of anatomy in bifurcation lesion disease, Proceedings 25th IEEE International Conference on High Performance Computing Workshops Hipcw 2018 (July, 2018), pp. 56-64 [doi]  [abs].
33. Gounley, J; Vardhan, M; Randles, A, A computational framework to assess the influence of changes in vascular geometry on blood flow, Pasc 2017 Proceedings of the Platform for Advanced Scientific Computing Conference (June, 2017), ACM Press [doi]  [abs].
34. Laurence, TA; Ly, S; Fong, E; Shusteff, M; Randles, A; Gounley, J; Draeger, E, Using stroboscopic flow imaging to validate large-scale computational fluid dynamics simulations, Progress in Biomedical Optics and Imaging Proceedings of SPIE, vol. 10076 (January, 2017), SPIE [doi]  [abs].
35. Gounley, J; Draeger, EW; Randles, A, Numerical simulation of a compound capsule in a constricted microchannel., Procedia computer science, vol. 108 (January, 2017), pp. 175-184 [doi]  [abs].
36. Gounley, J; Chaudhury, R; Vardhan, M; Driscoll, M; Pathangey, G; Winarta, K; Ryan, J; Frakes, D; Randles, A, Does the degree of coarctation of the aorta influence wall shear stress focal heterogeneity?, vol. 2016 no. 2016 (October, 2016), pp. 3429-3432, IEEE [doi]  [abs].
37. Randles, A; Draeger, EW; Oppelstrup, T; Krauss, L; Gunnels, J, Massively Parallel Models of the Human Circulatory System, http://dl.acm.org/citation.cfm?id=2807676, vol. 15-20-November-2015 (November, 2015), ACM [citation.cfm], [doi]  [abs].
38. Randles, A; Draeger, EW; Michor, F, Analysis of pressure gradient across aortic stenosis with massively parallel computational simulations, http://ieeexplore.ieee.org/document/7043018/ (September, 2014)  [abs].
39. Kale, V; Randles, A; Gropp, WD, Locality-optimized mixed static/dynamic scheduling for improving load balancing on SMPs, ACM International Conference Proceeding Series, vol. 09-12-September-2014 (September, 2014), pp. 115-116, ACM Press [doi]  [abs].
40. Randles, A; Rand, D; Lee, C; Morrisett, G; Pfister, H, Massively Parallel Model of Extended Memory Use In Evolutionary Game Dynamics (May, 2014), pp. 1217-1228, IEEE [doi]  [abs].
41. Randles, A; Kale, V; Hammond, JR; Gropp, W; Kaxiras, E, Performance analysis of the lattice Boltzmann model beyond Navier-Stokes (May, 2014), pp. 1063-1074, IEEE [doi]  [abs].
42. Randles, A, MIC-SVM: Designing A Highly Efficient Support Vector Machine for Advanced Modern Multi-Core and Many-Core Architectures, http://ieeexplore.ieee.org/abstract/document/6877312/ (January, 2014), pp. 809-818 [doi]  [abs].
43. Keyes, D; McInnes, LC; Woodward, C; Gropp, W; Myra, E; Pernice, M; (KAUST and Columbia Univ.); (Lawrence Livermore National Laboratory); (Univ. of Illinois at Urbana-Champaign); (Univ. of Mich.); (Idaho National Lab.), Multiphysics simulations: challenges and opportunities. (November, 2012), Office of Scientific and Technical Information (OSTI) [doi] .
44. Peters, A; Zeger, L, Efficient methods for broadcasting multi-slot messages with random access with capture, 2011 - MILCOM 2011 Military Communications Conference (November, 2011), pp. 1838-1844, IEEE [doi] .
45. Randles, A; Zeger, L, Efficient Resource Allocation for Broadcasting Multi-Slot Messages With Random Access with Capture (October, 2011), IEEE [available here] .
46. Randles, A; Melchionna, S; Kaxiras, E; Latt, J; Sircar, J; Bernaschi, M; Bisson, M; Succi, S, Multiscale simulation of cardiovascular flows on the IBM Bluegene/P: full heart-circulation system at red-blood cell resolution (November, 2010), ACM IEEE .
47. Randles, A, Parallel Genomic Sequence-Search on a Massively Parallel System, edited by Thorsen, O; Jiang, K; Smith, B; Lin, H; Feng, W; Sosa, CP (May, 2007), ACM .
48. Pang, Y-P; Swartz, B; Smith, B; Mullins, T; Peters, A; Musselman, R, Poster reception---Optimizing EUDOC for the IBM eServer Blue Gene supercomputer, Proceedings of the 2006 ACM/IEEE conference on Supercomputing - SC '06 (2006), pp. 174-174, ACM Press [doi] .