Amanda Randles, Alfred Winborne and Victoria Stover Mordecai Assistant Professor of Biomedical Sciences

My research in biomedical simulation and high-performance computing focuses on the development of new computational tools that we use to provide insight into the localization and development of human diseases ranging from atherosclerosis to cancer. 

Please note: Amanda has left the Mathematics department at Duke University; some info here might not be up to date.

Contact Info:

Office Location:	Wilkinson Building, Room No. 325, 534 Research Drive, Durham, NC 27708
Office Phone:	(919) 660-6962
Email Address:

Teaching (Spring 2026):

• BME 520L.001, COMP FOUND BIOMED SIMULATION Synopsis

  Hudson 218, TuTh 10:05 AM-11:20 AM

• BME 520L.01L, COMP FOUND BIOMED SIMULATION Synopsis

  Hudson 115A, F 03:05 PM-06:05 PM

Education:

Ph.D.

Harvard University

2013

Keywords:

Aortic Coarctation • Atherosclerosis • Biomechanical Phenomena • Biomechanics • Biophysics • Cancer • Cancer cells • Cardiovascular Diseases • Computational Biology • Computational fluid dynamics • Computer Simulation • Fluid mechanics • Hemodynamics • High performance computing • Lattice Boltzmann methods • Metastasis • Multiscale modeling • Muser Mentor • Parallel algorithms • Parallel computers

Recent Publications   (More Publications)

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]

Recent Grant Support

• iPediHeart: Interdisciplinary Research Training Program for Pediatric Heart Disease, National Institutes of Health, 2025/09-2030/08.      
• FDT-BioTech: Scalable Digital Twins to Power Virtual Trials and Test Treatments, National Science Foundation, 2025/09-2028/08.      
• Dynamic models of the cardiovascular system capturing years, rather than heartbeats, National Institute on Aging, 2022/09-2027/07.      
• University Training Program in Biomolecular and Tissue Engineering, National Institute of General Medical Sciences, 1994/07-2027/06.      
• Detection of Emergent Mechanical Properties of Biologically Complex Cellular States, University of California - Berkeley, 2023/03-2027/02.      
• Sony Women in Technology Award with Nature 2024: prize package, SPRINGER NATURE LIMITED, 2025/08-2026/08.      
• Data-Driven Approaches to Identify Biomarkers for Guiding Coronary Artery Bifurcation Lesion Interventions from Patient-Specific Hemodynamic Models, National Institutes of Health, 2022/09-2025/08.      
• CAREER: Scalable Approaches for Multiphysics Fluid Simulation, National Science Foundation, 2020/04-2025/03.      
• Computational Tools for Improving Stereo-EEG Implantation and Resection Surgery, National Institutes of Health, 2022/08-2024/05.      
• Using Computational Fluid Dynamics to Predict Aneurysmal Degeneration of the Distal Aorta After Repair of Type A Dissection, American Heart Association, 2022/01-2023/12.      
• Technology for efficient simulation of cancer cell transport, National Institutes of Health, 2020/08-2023/07.