June 23, 2026 | Randles Lab
The 2026 International Conference on Computational Science (ICCS) was held in Hamburg, Germany, June 29–July 1, 2026.
The Randles Lab presented research spanning high-performance computing, artificial intelligence, cardiovascular digital twins, and cellular-scale blood flow at the 2026 International Conference on Computational Science (ICCS) in Hamburg, Germany.
Amanda Randles delivered a keynote, “Chronophysiomics at Exascale: Building Longitudinal Digital Twins from Wearables to HPC,” exploring how longitudinal physiological data, patient-specific computational models, and exascale computing can be brought together to move digital twins beyond snapshots of a patient toward models that evolve over time.
The lab also presented three papers showcasing work across computational scales.
Ayman Yousef presented “Instrumenting Lightweight, Modular Machine Learning Training and Inference in Parallel Solvers,” co-authored with Corey Wetterer-Nelson, Mengjiao Han, Victor Mateevitsi, Joseph Insley, Silvio Rizzi, Janet Knowles, Michael Papka, and Amanda Randles. The work advances the integration of machine learning directly into large-scale parallel simulation workflows.
Shihab Kabir presented “Investigating the Influence of Red Blood Cell Heterogeneity on Cell Transport and Blood Flow Hemodynamics,” co-authored with Wendy Wu, Aristotle Martin, Wentao Ma, and Amanda Randles. The study investigates how variation within red blood cell populations influences cellular transport and blood-flow behavior, with implications for understanding the role of blood-cell heterogeneity in disease.
Kabir also presented “Multiscale Modeling of Shear-Dependent Tumor Cell Adhesion,” co-authored with Aristotle Martin, Wendy Wu, and Amanda Randles. The work examines how local hemodynamic forces influence circulating tumor cell adhesion within vascular networks, helping connect vessel-scale blood flow with cellular mechanisms involved in metastatic transport.
Together, the keynote and papers highlight the lab’s broader effort to build predictive computational models of human health across scales—from individual cells and vascular networks to millions of heartbeats and longitudinal physiological trajectories.