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Pengfei Song

Associate Professor of Biomedical Engineering
Biomedical Engineering
1427 Fitzpatrick Center, Box 90281, Durham, NC 27708

Overview


Dr. Pengfei Song conducted his PhD and postdoctoral training on the topics of ultrasound elastography and microvascular imaging under the supervisions of Drs. James Greenleaf and Shigao Chen at Mayo Clinic. Before joining Duke University, Dr. Pengfei Song was a Y. T. Lo Faculty Fellow and Associate Professor of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. His current research interests include ultrafast ultrasound imaging, super-resolution ultrasound, functional ultrasound, 3D ultrasound imaging, deep learning applied to ultrasound imaging, and ultrasound shear wave elastography. 

Dr. Song has published over 100 peer-reviewed journal papers with a Google Scholar total citation exceeding 6200 and an h-index of 42 (March 2025). He holds several patents that have been licensed and commercialized by major ultrasound companies and used worldwide in the clinic. Dr. Song has delivered over 30 invited presentations including twice at the Gordon Research Conference. He has been consistently ranked as an excellent instructor by his students.

Dr. Song is a recipient of the NIH K99/R00 Pathway to Independence Award, the NSF CAREER Award, the NIBIB Trailblazer Award, the IEEE Ultrasonics Early Career Investigator Award, the Chan Zuckerberg Initiative (CZI) Early Career Acceleration Award, and the Campus Distinguished Promotion Award at the University of Illinois.His research program has been continuously funded by NIH, DOD CDMRP, and NSF. He is an elected Fellow of the American Institute of Ultrasound in Medicine (AIUM), a Senior Member of the National Academy of Inventors(NAI), a Senior Member of IEEE, and a Full Member of the Acoustical Society of America (ASA). 

Current Appointments & Affiliations


Associate Professor of Biomedical Engineering · 2025 - Present Biomedical Engineering, Pratt School of Engineering

Recent Publications


Improved Microbubble Tracking for Super-Resolution Ultrasound Localization Microscopy using a Bi-Directional Long Short-term Memory Neural Network.

Journal Article bioRxiv · February 14, 2025 Ultrasound localization microscopy (ULM) enabled high-accuracy measurements of microvessel flow beyond the resolution limit of conventional ultrasound imaging by utilizing contrast microbubbles (MBs) as point targets. Robust tracking of MBs is an essential ... Full text Link to item Cite
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Recent Grants


Whole-brain Functional Super-Resolution Ultrasound Imaging

ResearchPrincipal Investigator · Awarded by Chan Zuckerberg Initiative · 2024 - 2027

Noninvasive Deep-Brain Neurovascular Imaging with Light and Sound

ResearchPrincipal Investigator · Awarded by Chan Zuckerberg Initiative · 2024 - 2025

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Education, Training & Certifications


Mayo Clinic · 2014 Ph.D.

External Links


Song Lab website