Amanda Randles and Mark Palmeri Elected to AIMBE College of Fellows

4/13/26 Awards 3 min read

The honor from the American Institute for Medical and Biological Engineering represents the top 2% of engineers in the field

Amanda Randles (left) and Mark Palmeri (right)
Amanda Randles and Mark Palmeri Elected to AIMBE College of Fellows

Amanda Randles, the Alfred Winborne Mordecai and Victoria Stover Mordecai Associate Professor, and Mark Palmeri, a professor of the practice in Duke University’s Department of Biomedical Engineering, were elected to the American Institute for Medical and Biological Engineering (AIMBE), an international non-profit organization representing the most accomplished individuals in the medical and biomedical fields of engineering.

Membership in the AIMBE College of Fellows represents the selective top 2% of medical and biological engineers. With the election of Randles and Palmeri, Duke BME is now home to more than two dozen AIMBE fellows.

Randles was recognized for her pioneering research to develop non-invasive, personalized digital twin technologies capable of transforming vascular disease diagnosis, monitoring, and treatment. This technology integrates wearable-informed computational models to provide personalized insights into cardiovascular hemodynamics and optimize treatment strategies. So far, Randles and her team have used this tool to model more than 700,000 heartbeats to better predict an individual’s risk of heart disease and heart attack.   

In addition to this work, Randles and her team developed a computational approach called the Adaptive Physics Refinement (APR) algorithm that captures cellular interactions and their effects on a cellular trajectory. With teams at the Lawrence National Laboratory, Randles has used APR to enhance the capabilities of computational models to stimulate the movement of individual cancer cells across the human body, essentially creating a window that could track how cancer cells collide and interact with blood cells as they move through the vasculature.

A testament to her dynamic work, Randles’s recent publication in Cardiovascular Engineering and Technology extends the HarVI digital twin framework to peripheral circulation to combat peripheral artery disease (PAD), specifically chronic limb-threatening ischemia (CLTI). By offering real-time predictions of hemodynamics, researchers can improve tracking revascularization outcomes to prevent limb loss.

Randles has received numerous awards and recognition for her pioneering work, including the inaugural Sony Women in Technology Award, the Association for Computing Machinery Prize in Computing, the National Institutes of Health Director’s Pioneer Award, the Grace Murray Hopper Award from the ACM, and is a fellow of the National Academy of Inventors.

Palmeri was recognized for his innovative medical device work as well as his leadership and mentorship of biomedical engineering students as they develop medical devices in programs like the BME Design Fellows.

As the founder of the BME Design Fellows program, Palmeri is a key figure in expanding Duke BME’s design curriculum. Throughout the program, teams of students work on collaborative projects to design and test medical instruments based on clinical needs identified by Duke Health physicians. The program has resulted in a multitude of devices, including a low-cost and easy-to-use tympanometer to screen children for hearing loss. His mentorship in this program has been honored by multiple awards of excellence, most recently the Capers and Marion McDonald Award for Excellence in Mentoring and Advising in 2025.

In addition to his teaching work, Palmeri’s research explores how ultrasound imaging can be used to characterize the ways in which soft tissues move and behave in response to ultrasound pulses. Palmeri’s most recent published work introduces an efficient mathematical model to understand how vibration waves move through tissues like muscle. By simplifying the wave behavior into two types, the model can accurately measure tissue properties while being much quicker than traditional simulation methods.