National Institute of Health Data Science
Institute for Artificial Intelligence
Peking University
Email: hongshenda@pku.edu.cn
Address: 38 Xueyuan Rd, Haidian District, Beijing, 100191, China
[Updated at 2025/02] We are recruiting PostDoc (Opening, Doctors of Public Health are more welcomed), Ph.D. (Two positions available for 2026 at School of Intelligence Science Technology (SIST, 智能学院)), and Interns (Opening always) who have a strong passion of AI for digital health with coding skills. If you are interested, please send email with your CV.
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
- Deep 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). 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).
- 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.
Working Experience
- 2024/09 - now, Assistant Professor, Institute for Artificial Intelligence, Peking University, Beijing, China
- 2022/08 - now, Assistant Professor, National Institute of Health Data Science, Peking University, Beijing, China
- 2020/09 - 2022/07, (Boya) Postdoctoral Researcher, National Institute of Health Data Science, Peking University, Beijing, China, working with Prof. Luxia Zhang
- 2020/02 - 2020/08, Visiting Researcher, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA, working with Prof. M. Brandon Westover
- 2019/09 - 2020/08, Postdoctoral Researcher, College of Computing, Georgia Institute of Technology, Atlanta, GA, USA, working with Prof. Jimeng Sun
- 2018/06 - 2018/08, Research Intern, Tencent Medical AI Lab, Beijing, China
- 2017/07 - 2018/02, Research Intern, IBM China Research Lab, Beijing, China
- 2016/10 - 2017/04, Research Intern, Microsoft Research Asia, Beijing, China
Education
- 2014/09 - 2019/07, Ph.D., Computer Sciences, Peking University, Beijing, China, advisor Prof. Hongyan Li
- 2010/09 - 2014/07, B.S., Mathematics, Beijing University of Posts and Telecommunications, Beijing, China
- 2007/09 - 2010/06, Science Honor Class, Hefei No.1 High School, Hefei, Anhui
News
[2025/01] One paper published in European Heart Journal - Digital Health
[2025/01] Two papers accepted to ICLR 2025
[2024/12] One paper published in npj Cardiovascular Health
[2024/09] One paper accepted to NeurIPS 2024
[2024/09] Two papers published in npj Women's Health
[2024/08] We successfully organized the KDD-AIDSH Workshop KDD-AIDSH Workshop (AI and Data Science for Healthcare) in Barcelona
[2024/07] One paper published in PNAS
Recent Publications
See full publications at Google Scholar, DBLP, and PubMed
(#Equal contribution; *Corresponding author)
[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
[EHJ Digital Health 2025] Yirao Tao, Deyun Zhang, Naidong Pang, Shijia Geng, Chen Tan, Ying Tian, Shenda Hong*, XingPeng Liu*. Multi-Modal Artificial Intelligence Algorithm for the Prediction of Left Atrial Low-Voltage Areas in Atrial Fibrillation Patient Based on Sinus Rhythm Electrocardiogram and Clinical Characteristics: A Retrospective, Multicenter Study. European Heart Journal - Digital Health, 2024;, ztae095
[npj Systems Biology and Applications 2025] Shuhao Mei, Xin Li, Yuxi Zhou*, Jiahao Xu, Yong Zhang*, Yuxuan Wan, Shan Cao, Qinghao Zhao, Shijia Geng, Junqing Xie, Shengyong Chen*, Shenda Hong*. Deep Learning for Detecting and Early Predicting Chronic Obstructive Pulmonary Disease from Spirogram Time Series . npj Syst Biol Appl 11, 18 (2025)
[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)
[npj Women's Health 2024] Zenghui Lin, Xintong Liu, Nan Wang, Ruichen Li, Qingao Liu, Jingying Ma, Liwei Wang*, Yan Wang*, Shenda Hong*. Deep Learning with Information Fusion and Model Interpretation for Long-term Prenatal Fetal Heart Rate Data. npj Womens Health 2, 31 (2024)
[Lancet Digital Health 2024] Shenda Hong*, Qinghao Zhao. Expanding Electrocardiogram Abilities for Postoperative Mortality Prediction with Deep Learning. 6(1): e4-e5
[PNAS 2024] Zhiguang Liu#, Minkun Cai#, Shenda Hong#, Junli Shi#, Sai Xie, Chang Liu, Huifeng Du, James D Morin, Gang Li, Liu Wang, Hong Wang, Ke Tang, Nicholas X Fang, Chuan Fei Guo. Data-driven Inverse Design of Flexible Pressure Sensors. Proceedings of the National Academy of Sciences 121, no. 28 (2024): e2320222121
[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
[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
Teaching
- Basis of Python Programming in Health Data Science (for undergraduate students, graduate students and continuing education of clinicians)
Awards
- 2021/09, Top-Cited Paper Awards (Top 1%), IOP Publishing
- 2020/12, Boya Postdoctoral Fellowship (Peking University)
- 2019/10, Golden Award, China “Internet+” Innovation and Entrepreneurship Competition
- 2017/09, First Place in the 18th PhysioNet/Computing in Cardiology Challenge [code] [paper]
Services
Associate Editor
Conference Reviewer
- ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD) 2022-2025
- International Conference on Learning Representations (ICLR) 2021-2025
- International Conference on Machine Learning (ICML) 2021-2025
- Conference on Neural Information Processing Systems (NeurIPS) 2020-2025
- AAAI Conference on Artificial Intelligence (AAAI) 2020-2025
- International Joint Conference on Artificial Intelligence (IJCAI) 2019-2020
Others
- External reviewer of Center for Medical Device Evaluation (National Medical Products Administration, NMPA) of China
Team
Research Staff
- Deyun Zhang (2021-)
- Shijia Geng (2021-)
PostDoc
- Haixue Wang (2023-)
Ph.D. Students
- Jiarui Jin (2025-, co-supervise with Prof. Hongyan Li)
- Guangkun Nie (2025-, co-supervise with Prof. Hongyan Li)
- Mingke Yan (2025-)
- Donglin Xie (2024-)
- Gongzheng Tang (2023-)
Research Assistant
- Jun Li (2022-)
Last update: 2025/02