Our lab primarily focuses on the following two areas of research:
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Deep learning for temporal medical data: temporal events, time series (e.g. longitudinal data, cohort, electronic health records), and physiological signals (e.g. ECG, EEG, PPG, PCG, PSG). We won the first place of the 18th PhysioNet/Computing in Cardiology Challenge, and released a DNN backbone Net1D. Currently working on learning in label scarce environment, generative methods, integrating with medical knowledge and other modality data (e.g. texts).
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Digital health: enhancing smart devices with AI and applications in healthcare, portable ECG device, flexible ECG patch, smart watch (with PPG/ECG sensor), smart ring (with PPG sensor), smart stethoscope (with PCG sensor), smart eyemask (with EEG sensor). Currently collaborating closely with affiliated hospitals of Peking University, working on smart devices for sleep disorders, cardiovascular disease, and fetal monitoring.
[Updated at 2025/11] We are recruiting team members who have a strong passion of AI for digital health: 1) PostDoc (Opening) with clinical research methodology and writing skills, coding skills not required; 2) Ph.D. (Positions available for 2027 at School of Intelligence Science Technology (SIST, 智能学院)); 3) Research Assistant with proficient coding skills. If you are interested, please send an email with your CV attached.