Lei li

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Dr. Lei Li is an incoming Assistant Professor of Electrical Computer Engineering at Rice University. His primary research interest is to build next-generation medical imaging devices to better understand the brain and more clearly perceive disease states. He has developed advanced photoacoustic computed tomography (PACT)—an non-invasive imaging modality that combines light and sound for deep-tissue imaging—to visualize wholebody dynamics, map whole-brain functional connectivity, and diagnose human breast cancer. He has developed a PACT-guided microrobotic system to navigate and control microrobots inside the body for drug delivery. He has also integrated photoswitchable proteins with PACT to monitor tumor metastasis and visualize intratumor protein interactions. Pushing the benchtop photoacoustic system toward wearable devices, he introduced ergodicity into PACT and developed a high-throughput imaging system with significantly reduced size and complexity, promising wearable applications.

Dr. Li obtained his Ph.D. from the Department of Electrical Engineering at California Institute of Technology (Caltech) in 2019. He then continued his research at Caltech as a postdoctoral scholar in the Department of Medical Engineering. He will join Rice in Jan 2023 as part of the Rice Digital Health Initiative.

Research Areas

Biophotonics, Medical Imaging, Neuroimaging, Artificial Intelligence, Computational Imaging, Image Reconstruction, Biomedical Instrumentation, Medical Devices, Optical Sensing.

Industry Impact & Relevance

Dr. Li’s overarching research goal is to develop new biomedical imaging technology that combines light, sound, and artificial intelligence to visualize deep brain functions, diagnose early-stage cancer and navigate microrobots for internal surgery. His research focuses on developing new photoacoustic (PA) and ultrasonic (US) technology and combining them with artificial intelligence to enable diverse biomedical applications, including novel whole-brain imagers visualizing brain functions and diagnosing brain disease, PA/US navigated robotic systems guiding and controlling microrobots inside the body for surgery or drug delivery, as well as wearable devices continuously monitoring early-stage cancer patients and detecting circulating tumor cells.


2019, PhD in Electrical Engineering, California Institute of Technology

2016, MS in Electrical and System Engineering, Washington University in St. Louis

Honors & Awards

2021 Rising Stars in Engineering in Health, Columbia University and Johns Hopkins University

2021 TED Fellowship, TED Fellows Program

2020 Charles and Ellen Wilts Prize, California Institute of Technology

2020 Seno Medical Best Paper Award, SPIE Photonics West Photons Plus Ultrasound: Imaging and Sensing

2019 MIT Technology Review Innovators Under 35 (China), MIT Technology Review

2017 Seno Medical Best Paper Award, SPIE Photonics West Photons Plus Ultrasound: Imaging and Sensing


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