[Updated at 2025/06] 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) Research Assistant with proficient coding skills. If you are interested, please send an email with your CV attached.
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 digital 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
Working Experience
Education
[2025/06] We will host the BIBM Workshop (LLM in Healthcare) in Wuhan, China
[2025/06] Two papers about ECG foundation model and EEG spike detection accepted to NEJM AI
[2025/06] One paper about text to ECG generation accepted to Cell Patterns
[2025/04] Invited to serve as an associate editor for npj Digital Medicine
[2025/04] One paper about PSG sleep depth index published in npj Digital Medicine
[2025/01] One paper about AI-ECG published in European Heart Journal - Digital Health
[2025/01] Two papers about ECG-LLM and imbalance regression accepted to ICLR 2025
[2024/08] We successfully organized the KDD-AIDSH Workshop (AI and Data Science for Healthcare) in Barcelona
[2024/07] One paper about AI for sensor design published in PNAS
[2024/01] Three papers accepted to ICLR 2024
[2024/01] AIMEL (AI in Medcine League) organized its first seminar at Peking University Health Science Center
[2023/12] An invited comment published in The Lancet Digital Health
[2023/11] Lab member Guangkun Nie is funded by the Natural Science Foundation of Beijing (2023年度北京市自然科学基金本科生“启研”计划项目). Congrats!
See full publications at Google Scholar, DBLP, and PubMed
(*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