Amanda Randles, PhD, director of the Duke Center for Computational and Digital Health Innovation and professor of biomedical engineering, and her laboratory have developed HARVEY, a computational fluid dynamics platform that creates personalized models of blood flow from medical imaging.
The HARVEY platform leverages supercomputing, physics-based simulations, and wearable device data to monitor real-time hemodynamics and spot heart failure early.
Even on the largest supercomputers, simulations that explicitly resolve every blood cell can only cover a small volume. Amanda Randles and her team at Duke University set out to solve this problem by creating a physics-based technique called Adaptive Physics Refinement (APR) that can capture a much larger stretch of vessel by splitting the domain into a high-resolution ‘moving window’ and a low-resolution bulk fluid.
Center director Amanda Randles explains how the role of computational models in drug discovery is beginning to change.
Center director Amanda Randles is featured in this Nature Biology article about the FDA’s drive to reduce animal testing in drug development through AI-powered biosimulation techniques such as multi-agent virtual scientists and digital twins.
Research by Maria Gorlatova, the Center’s Associate Director for Extended Reality, and The Athena AI Institute team has received the 2025 Best Paper Award for IEEE Transactions on Visualization and Computer Graphics in the area of “Virtual Reality & Augmented Reality” by the IEEE Computer Society Publications Board. According to the Athena AI Institute, Dr….
At the 2026 Peace Ambassador Leadership Summit (PALS) through National Voices for Equality Education and Enlightenment (NVEEE), BIG IDEAs Lab’s Community Engagement Team – Kaileigh Moertl, Lauren Lederer, Hayoung Jeong, Yihang Jiang, and Annika Kumar – led the “Collect and Build Your Own Digital Biomarkers” workshop with approximately 20 high school students from across the…
Jessilyn Dunn and the BIG IDEAs Lab team had a fantastic time at the Association for Health Learning and Inference CHIL 2026 in Seattle, connecting with researchers and clinicians working at the intersection of machine learning, health, and biomedicine.
Members of the Duke Center for Computational and Digital Health Innovation leadership team have reached some exciting milestones.
Duke researchers, including the Center’s Associate Director for Wearable Technology Jessilyn Dunn, highlight the gaps in federal guidance governing validation of wearable devices.