Li Zhu
Digital Health Researcher & AI Innovator
Li Zhu is a digital health researcher and AI innovator, transforming human physiology into scalable intelligence. His work spans wearable sensing, foundation models, and clinical validation.
His research has been featured on the IEEE JBHI journal cover, and he has authored 50+ publications at top-tier venues with 15+ patents filed. His work spans cuffless blood pressure monitoring, contactless vital sign detection, atrial fibrillation burden estimation, and advanced bio-sensing technologies.
He received his Ph.D. in Electrical and Computer Engineering from Rutgers University in 2018, where he developed computational methods for predicting behavior from neuroimaging data. Prior to his Ph.D., he spent nearly a decade in the consumer electronics industry in China, including five years leading a 20+ member multidisciplinary team in hardware design and product development.
Research Impact
Featured Research
Atrial Fibrillation Detection & Burden Estimation
Smartwatch-based algorithms for continuous AFib monitoring, from data collection to clinical validation and product deployment.
Contactless Vital Sign Monitoring
AI models that estimate heart rate, respiration rate, and SpO2 from facial video using standard smartphone cameras.
Cuffless Blood Pressure Monitoring
Machine learning-based BP estimation using ear-worn PPG and inertial sensors, with clinical validation across multiple devices.
Neuroimaging & Brain-Computer Interface
Visibility graph analysis and fNIRS signal processing methods for decoding cortical brain states from widefield transcranial imaging.
