Amanda Randles

Digital Library

ACM Prize in Computing

USA - 2023

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Ground-breaking contributions to computational health through innovative algorithms, tools, and high performance computing methods for diagnosing and treating a variety of human diseases

Amanda Randles is at the forefront of creating vascular digital twins, bringing computational health advancements to the forefront of medical practice. While cardiovascular research has grown, the medical community still faces challenges in developing precise and detailed models of vascular systems for clinical application. Randles' work addresses these gaps by pushing the boundaries of what can be achieved with high performance computing (HPC) and cloud technology in simulating 3D hemodynamics. Her contributions not only enhance our understanding of vascular dynamics but also strive to expand the spatial and temporal scales at which these systems can be modeled, critical steps towards their clinical translation. Her work provides a strong foundation for using computational tools to aid in diagnosing and treating human disease.


Expanding the scope of domain modeled: Her first major achievement in computational blood flow models was in 2010 when her team conducted the inaugural simulation of the coronary arterial tree at a cellular resolution across a full heartbeat.  She built on this experience by developing HARVEY, a massively parallel computational fluid dynamics software for calculating patient-specific blood flow maps. The code was named after William Harvey, who first discovered the circulation of blood. By utilizing 1.5 million computing cores of the Lawrence Livermore National Laboratory's Sequoia supercomputer, she performed the first full-body scale simulation of 3D blood flow. Randles' leadership in method development has further optimized the use of heterogeneous supercomputers and cloud computing resources, culminating in multiscale models significantly reducing computational demands. The resulting reductions in both time and energy make clinical translation of such tools easier.


In her work with HARVEY, Randles and her team introduced a novel moment-based representation technique that reduces memory usage, thus reducing the computational hardware required for high-resolution simulations.  This innovation allows for a larger patient cohort to be modeled.  Furthermore, her research has resulted in a suite of influential publications underscoring the necessity of detailed models encompassing the complete 3D arterial tree including side branches to accurately reflect the nuances of blood flow and heart disease. These enhanced models offer more precise, personalized simulations and can enable clinical trials to cover conditions previously excluded.  Randles' work has helped quantify when complete 3D models are needed as opposed to reduced order alternatives.  

Bridging scales through multiscale modeling: Randles has significantly contributed to fluid-structure-interaction modeling as well. Randles and her team crafted a computational method tailored to distinct cell types, confirming the model's accuracy against microfluidic experimental data for both cancerous and red blood cells. Her team then pioneered techniques that scale to simulate hundreds of millions of cells using leadership class heterogeneous computing architectures.  Tackling the computational challenge of simulating cell behavior across vast spatial scales, from the microscopic to the potentially macroscopic, her team has developed the Adaptive Physics Refinement (APR) method.  This innovative approach allows for the study of cellular interactions over large distances that could determine why certain cancer cells metastasize to specific locations. Traditional models, even when run on the most advanced supercomputers, are limited to representing a few cubic millimeters with detailed 3D deformable cells.  The APR method surmounts this limitation without compromising accuracy. This advancement is important for elucidating underlying mechanisms driving disease and could significantly impact our understanding of disease initiation and progression.

Randles' further contributions to the field of computational health include methods integrating machine learning and physics-based simulations. She specifically addresses how comorbidities like anemia or hypertension impact hemodynamics in cardiovascular diseases. Her work using massively parallel computing offers predictive insights into the exacerbating effects of exertion and other physiological factors on patients with conditions such as coarctation of the aorta.

Building upon these methodologies, Randles' team created novel longitudinal hemodynamic maps by developing an algorithm that extends the time frame of simulations from seconds to weeks. Introducing a novel computational method to drive the flow simulations from wearable biosensor data, this work lays the foundation for a comprehensive view of a patient's vascular health over time, driven by wearable biosensor data, thus pioneering a new direction in computational health.

Press Release

ACM Distinguished Member

USA - 2023

Press Release

ACM Senior Member

USA - 2022

ACM Grace Murray Hopper Award

USA - 2017

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For developing HARVEY, a massively parallel circulatory simulation code capable of modeling the full human arterial system at subcellular resolution and fostering discoveries that will serve as a basis for improving the diagnosis, prevention, and treatment of human diseases.

Amanda has established an ambitious research program focused around the transformation of her circulatory modeling code HARVEY into a world-class research tool capable of making a direct clinical impact. HARVEY is a massively parallel circulatory simulation code capable of modeling the full human arterial system at subcellular resolution. Her work leverages high performance computing to solve biomedical problems. She has developed large-scale computational methods to study disease localization and progression to foster discoveries that will serve as a basis for improving the diagnosis, prevention, and treatment of human diseases.

Together with an interdisciplinary team of doctors, scientists, and computer scientists Amanda has developed several new methods of high-performance computer simulations for blood flow in arteries across multiple scales  from molecules to blood cells. She has been applying theories from cosmology to the simulation of the forces from the beating heart. She developed her own parallel application code (HARVEY) to model flow in microfluidic devices and aneurysms as well as in coronary arteries. Amanda's multi-disciplinary background in applied physics and of computational methods and parallelization strategies in computer science, serves her well in these endeavors.

Amanda has remained keenly aware of the need to translate computational results into actionable data doctors can use to improve patient outcomes, and has continued to build collaborations that will allow her use this new computational capability to bridge the gap from the computer to the clinic. Her cross-disciplinary approach will yield new insights into efficient fluid flow simulations for complex multi-scale systems that will be useful well beyond blood flow simulations.

Press Release

ACM-IEEE CS George Michael Memorial HPC Fellowships

USA - 2012

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Multiscale Hemodynamics

ACM-IEEE CS George Michael Memorial HPC Fellowships

USA - 2010

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Multiscale simulation of cardiovascular flows on the IBM Bluegene/P: full heart-circulation system at red-blood cell resolution

ACM-IEEE CS George Michael Memorial HPC Fellowships

USA - 2009

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Cardiovascular Disease

2023 ACM Prize in Computing

ACM named Amanda Randles the recipient of the ACM Prize in Computing for groundbreaking contributions to computational health through innovative algorithms, tools, and high-performance computing methods for diagnosing and treating a variety of human diseases.

Randles is the Alfred Winborne and Victoria Stover Mordecai Associate Professor of Biomedical Sciences at Duke University’s Pratt School of Engineering. She is known for developing new computational tools to harness the world’s most powerful supercomputers to create highly precise simulations of biophysical processes. Her early work included creating accurate 3D simulations of how blood flows through the circulatory system. More recently, she and her team developed biomedical simulations that yield direct and concrete impacts on patient care, including simulations of 700,000 heart beats (the previous state-of-the-art was of 30 heart beats), the interaction of millions of cells, and cancer cells moving through the body.

The ACM Prize in Computing recognizes early-to-mid-career computer scientists whose research contributions have fundamental impact and broad implications. The award carries a prize of $250,000 from an endowment provided by Infosys Ltd., a global leader in next-generation digital services and consulting.

Simulations of Blood Flow and Heart Research

Though still early in her career, Randles has led her field in developing computational tools to enable high-accuracy 3D blood flow simulations to diagnose and treat a variety of human diseases. Her major contributions to the field have included developing the first simulation of the coronary arterial tree at the cellular level for an entire heartbeat, using 1.5 million computer processing units (CPU’s) to simulate blood flow across the scale of the whole human body, and using trained machine learning models to develop a framework for predicting key hemodynamic metrics under new conditions. She also developed a new way to model the human heart, which allowed heart simulations for a large group of patients. In turn, these simulations led to a series of papers in which she demonstrated that, to model complex flow phenomena, it is essential to take into account the full arterial tree including its side branches. Randles’s full 3D simulations can also be used by cardiologists to plan therapeutic procedures. For example, with these simulations, doctors can determine, non-invasively, which coronary artery lesions need treatment, or perhaps how coronary artery hemodynamics may be impacted by the placement of a rigid metal stint into a flexible artery.

Randles’s algorithm to simulate 700,000 heartbeats was developed using wearable data-collection devices to capture a complete profile of a person’s circulatory state during normal activity. This was a major advancement of the existing method, which relied on standalone snapshots captured in atypical environments such as a doctor’s office.

Work in Fluid Structure Interaction

As part of her broader work in using computers to better understand physiology, Randles has made specific contributions to fluid structure interaction, which studies the physics of a fluid interacting with a solid structure (such as the friction of blood with a vein wall). One of her major efforts in this area has been working with her team to develop the adaptive physics refinement (APR) framework for capturing cellular-scale interactions over the millimeter length scale. APR is a breakthrough technology that allows cellular mechanics to be captured in 3D over long length-scales, dramatically reducing computational costs (the time and energy required for the computation) and enabling simulations to capture traversal distances that were previously impossible. Importantly, APR increased the volume of fluid captured at cellular resolution by at least five orders of magnitude. In other work in fluid structure interaction, Randles’s group developed a computational method that can be tuned to specific cell types. They validated this new model by comparing data from microfluidic experiments for cancer cells and red blood cells. Randles and her team also developed novel methods to enable the movements of hundreds of millions of cells to be processed on heterogeneous architectures (advanced hardware systems that integrate computer processing units and graphics processors).

Promise for Tumor Research and Cancer Prevention

Randles’s computational tools for modeling the cardiovascular system can also be used to understand how tumors metastasize. She is working on developing simulations down to a single cell and the smallest blood vessel, which will track what organs tumor cells will reach through circulation. Oncologists will be able to use her models in decision-making. Her models will also better facilitate the testing of new implant devices that are being developed to filter metastatic cells.

International Computing Society Recognizes 2023 Distinguished Members for Significant Achievements

ACM has named 52 Distinguished Members for significant contributions. All the 2023 inductees are longstanding ACM Members and were selected by their peers for work that has advanced computing, fostered innovation across various fields, and improved computer science education.

“The ACM Distinguished Members program recognizes both career achievement as well as participation in ACM,” said ACM President Yannis Ioannidis. “Many of these new 52 Distinguished Members have been selected for important technical achievements, while others have been chosen because of their service and/or work in computer science education, which lays the foundation for the future of our field. With the Distinguished Member designation, ACM also highlights how individual computing professionals maintain the health and growth of a global scientific society through membership and active engagement with their colleagues.” v vThe 2023 ACM Distinguished Members work at leading universities, corporations and research institutions in Australia, Belgium, Canada, China, Denmark, Finland, France, Germany, India, Israel, Italy, Switzerland, the United Kingdom, and the United States. This year’s class of Distinguished Members made advancements in areas including AI and economics, principles of data management, software development, human-computer interaction, developing technology for people with disabilities, mobile and wireless sensing systems, and many others.

The ACM Distinguished Member program recognizes up to 10 percent of ACM worldwide membership based on professional experience and significant achievements in the computing field. To be nominated, a candidate must have at least 15 years of professional experience in the computing field, five years of professional ACM membership in the last 10 years, and must have achieved a significant level of accomplishment or made a significant impact in the field of computing. A Distinguished Member is expected to have served as a mentor and role model by guiding technical career development and contributing to the field beyond the norm.

Read the ACM news release.

2017 ACM Grace Murray Hopper Award

ACM named Amanda Randles recipient of the ACM Grace Murray Hopper Award for developing HARVEY, a massively parallel fluid dynamics simulation capable of modeling the full human arterial system at subcellular resolution and fostering discoveries that will serve as a basis for improving the diagnosis, prevention, and treatment of human diseases. A focus of Randles’s research has been in developing and applying high performance computing to biomedical problems. With HARVEY, she combined her knowledge of applied physics, computational methods and parallel computing to develop a physiologically accurate model of the movement of red blood cells throughout the body. The simulation mapped 500 billion fluid points using a supercomputer with 1.6 million cores (individual processors). HARVEY marked the first time a researcher had been able to effectively model the flow of blood at the cellular level. Randles is presently working with collaborators at the Dana Farber Cancer Institute and Harvard Medical School to extend the use of HARVEY to cancer biology and cardiovascular treatment planning. Randles’s cross-disciplinary approach has helped to bridge the gap between the computer and the clinic—translating computational results into actionable data physicians can use to improve patient outcomes.

The ACM Grace Murray Hopper Award is given to the outstanding young computer professional of the year, selected on the basis of a single recent major technical or service contribution. This award is accompanied by a prize of $35,000. The candidate must have been 35 years of age or less at the time the qualifying contribution was made. Financial support for this award is provided by Microsoft.