Education & Postdoctoral Training
2020/09 - 2022/07, Peking University, National Institute of Health Data Science, Boya Postdoctoral Researcher
2020/02 - 2020/08, Harvard Medical School, Massachusetts General Hospital, Visiting Scholar
2019/09 - 2020/08, Georgia Institute of Technology, School of Computational Science and Engineering, Postdoctoral Researcher
2014/09 - 2019/07, Peking University, School of Electronics Engineering and Computer Science, Intelligence Technology and Science, Doctor of Philosophy
2010/09 - 2014/06, Beijing University of Posts and Telecommunications, School of Science, Mathematics, Bachelor of Science
Editorial Board
npj Digital Medicine, Associate Editor
SPJ Health Data Science, Associate Editor
Major Awards and Honors
Top-Cited Paper Awards (Top 1%), IOP Publishing, 2021/09
Peking University Boya Postdoctoral Fellowship, 2020/12
National Golden Award of the “Internet+” Innovation and Entrepreneurship Competition, 2019/10
First Place of the 18th PhysioNet/Computing in Cardiology Challenge, 2017/09
Narrative Report of Research Contributions
Shenda Hong is an Assistant Professor (tenure-track) at National Institute of Health Data Science, and Institute for Artificial Intelligence, Peking University. His research interests focus on deep learning for temporal medical data, including electronic health records and biosignals (e.g., ECG, PPG, EEG, PSG, PCG, FHR). He is also dedicated to AI for digita health, enhancing smart devices with AI, and developing applications for clinical practice. Additionally, he serves as an associate editor of npj Digital Medicine, SPJ Health Data Science, and as a reviewer for top-tier AI conferences, including ICLR, NeurIPS, ICML, KDD, AAAI, and IJCAI.
Research Interests
lDeep learning for temporal medical data: temporal events, time series (e.g. longitudinal data, cohort, electronic health records), and physiological signals (e.g. ECG, PPG, EEG, PSG, PCG, FHR, Spirogram). 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, LLM and other modality data (e.g. texts).
AI for digital health: enhancing smart devices with AI and applications in healthcare, portable ECG device, flexible ECG patch, ECG pad, 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.
We are recruiting team members who have a strong passion of AI for digital health: 1) PostDoc with clinical research methodology and writing skills, coding skills not required; 2) Ph.D. and Research Assistant with proficient coding skills. If you are interested, please send an email with your CV attached.
BIBLIOGRAPHY(Full Paper List at https://scholar.google.com/citations?user=K95az5UAAAAJ)
(* corresponding author)
[NEJM AI 2025] Jun Li, Aaron D. Aguirre, Valdery Moura Junior, Jiarui Jin, Che Liu, Lanhai Zhong, Chenxi Sun, Gari Clifford, M. Brandon Westover, Shenda Hong*. An Electrocardiogram Foundation Model Built on over 10 Million Recordings. NEJM AI, 2, 7, (2025)
[NEJM AI 2025] Jun Li, Daniel M. Goldenholz, Moritz Alkofer, Chenxi Sun, Fabio A. Nascimento, Jonathan J. Halford, Brian C. Dean, Mattia Galanti, Aaron F. Struck, Adam S. Greenblatt, Alice D. Lam, Aline Herlopian, Chinasa Nwankwo, Dan Weber, Douglas Maus, Hiba A. Haider, Ioannis Karakis, Ji Yeoun Yoo, Marcus C. Ng, Olga Selioutski, Olga Taraschenko, Gamaleldin Osman, Roohi Katyal, Sarah E. Schmitt, Selim Benbadis, Sydney S. Cash, William O. Tatum, Zubeda Sheikh, Wan Yee Kong, Grace Bayas, Niels Turley, Shenda Hong*, M. Brandon Westover*, Jin Jing*. Expert-Level Detection of Epilepsy Markers in EEG on Short and Long Timescales. NEJM AI, 2, 7, (2025)
[npj Digital Medicine 2025] Songchi Zhou, Ge Song, Haoqi Sun, Yue Leng, M. Brandon Westover, Shenda Hong*. Continuous Sleep Depth Index Annotation with Deep Learning Yields Novel Digital Biomarkers for Sleep Health. npj Digital Medicine 8, 203 (2025)
[Cell Patterns 2025] Yongfan Lai, Jiabo Chen, Deyun Zhang, Yue Wang, Shijia Geng, Hongyan Li, Shenda Hong*. DiffuSETS: 12-lead ECG Generation Conditioned on Clinical Text Reports and Patient-Specific Information. Patterns 6, 101291 (2025)
[ICLR 2025] Jiarui Jin, Haoyu Wang, Hongyan Li*, Jun Li, Jiahui Pan*, Shenda Hong*. Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model. International Conference on Learning Representations (ICLR) 2025
[ICLR 2025] Guangkun Nie, Gongzheng Tang, Shenda Hong*. Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint. International Conference on Learning Representations (ICLR) 2025
[ICLR 2024] Chenxi Sun, Yaliang Li, Hongyan Li*, Shenda Hong*. TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series. International Conference on Learning Representations (ICLR) 2024
[Lancet Digital Health 2024] Shenda Hong*, Qinghao Zhao. Expanding Electrocardiogram Abilities for Postoperative Mortality Prediction with Deep Learning. The Lancet Digital Health 6, no. 1 (2024): e4-e5
[npj Cardiovascular Health 2024] Jiarong Chen, Wanqing Wu, Tong Liu, Shenda Hong*. Multi-Channel Masked Autoencoder and Comprehensive Evaluations for Reconstructing 12-Lead ECG from Arbitrary Single-Lead ECG. npj Cardiovasc Health 1, 34 (2024)
[Cell Patterns 2023] Chenxi Sun, Hongyan Li*, Moxian Song, Derun Cai, Baofeng Zhang, Shenda Hong*. Continuous Diagnosis and Prognosis by Controlling the Update Process of Deep Neural Networks. Patterns 4(2), 100687
