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Mohamed (Moe) Elgendi is an Assistant Professor in Biomedical Engineering and Biotechnology at Khalifa University. He holds extensive experience in biomedical engineering with a focus on AI-driven innovations for health. His expertise includes wearable technologies, contact and non-contact biomedical sensing, textiles, machine learning, algorithm development, data analysis, health data visualization, and knowledge translation. He received specialized training in data analytics from MIT.
Previously, Dr. Elgendi served as Deputy Director of the Biomedical and Mobile Health Technology Lab at ETH Zurich, where he contributed to establishing the lab, mentoring students, and developing course materials. He has also held positions at Nanyang Technological University, the University of Alberta, and the University of British Columbia. Dr. Elgendi has been ranked among the top 2% of scientists worldwide by Stanford University in multiple years including 2021 through 2025. He serves on the editorial boards of several journals, has published over 170 scientific works, and has secured numerous competitive grants. He has supervised more than 40 MSc and BSc thesis students, many of whom have secured PhD scholarships at institutions such as MIT and Harvard. He heads the Digital Medicine Lab at Khalifa University.
Khalifa University's groundbreaking Hb-PPG dataset, published in Nature Scientific Data, enables precise non-invasive hemoglobin monitoring using four-wavelength PPG signals from 252 subjects.
Khalifa University researcher Mohamed Elgendi contributes to Hb-PPG dataset enabling accurate non-invasive hemoglobin estimation via multi-wavelength PPG, advancing anemia screening worldwide.
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