Recruitment Announcement [2026/05]
We are recruiting team members who have a strong passion of AI for digital health. If you are interested, please send an email with your CV attached:
- PostDoc with clinical research methodology and writing skills, coding skills not required
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 AI for Digital Health, including electronic health records (EHRs) and biosignals (e.g., ECG, PPG, PCG, EEG, PSG, FHR, Spirogram), enhancing smart devices with AI, and developing applications and validations 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.
Current Research Interests
- AI-Med Datasets. Constructing large-scale, multi-source biomedical databases to provide the foundational data infrastructure for training, benchmarking, and validating biosignal AI models across diverse clinical populations.
- Biosignal Foundation Models. Developing generalist foundation models by leveraging large-scale, multi-modality databases to enable robust representation learning and zero-shot generalization across diverse clinical tasks.
- Biosignal Specialized MLLMs and Agents. Constructing domain-specific multimodal large language models and clinical agents to bridge the semantic gap between time-series biosignals and clinical language, and to enable tool-augmented clinical reasoning and decision support.
- Digital Biomarker Discovery. Establishing a systematic paradigm to transform high-dimensional biosignals into structured, quantifiable metrics that capture latent physiological aging, organ function, and disease risk.
- AI-enhanced Health Devices. Inventing and enhancing AI-ECG products, device-repurposing techniques, and generative pipelines to expand the diagnostic capacity of low-cost, ubiquitously deployable sensors.
- Real-World Clinical Validation. Conducting rigorous real-world studies to evaluate the clinical efficacy and implementation pathways of AI-ECG interventions.
| Direction |
Category |
Works |
| AI-Med Datasets |
— |
HEEDBSci Data'26, MEETISci Data'26, MieDB-100k |
| Biosignal Foundation Models |
— |
ECGFounderNEJM AI'25, AnyECG, AnyPPGKDD'26, SleepFounder, SpikeNet2NEJM AI'25, DeepSpironpj Syst Biol Appl'25, FHRFounder |
| Biosignal Specialized MLLMs and Agents |
MLLMs |
HeartLangICLR'25, GEMNeurIPS'25, ECG-R1ICML'26, UniECG, SpiroLLMPLOS DH'25 |
| Agents & platforms |
KidneyTalk, ZhunXin, HeartOS |
| Digital Biomarker Discovery |
Aging |
PPGageCommun Med'25, ECGage, CTGage |
| Indices & omics |
Sleep Depth Indexnpj Digit Med'25, ECGomicsHDS'25 |
| Disease risk |
PPG-AVD, Spiro-RHF |
| AI-enhanced Health Devices |
问心无恙 hardware |
Portable ECG Device, Flexible ECG Patch, ECG Pad |
| Device-repurposing |
Holter-to-Sleep, AnyECG-Echo, AnyECG-Lab, ECG-to-CCTA |
| Rich-Data-from-Poor-Data |
DiffuSETS (Text-to-ECG)Patterns'25, PPGFlowECG, MCMA (ECG1to12)npj Cardiovasc Health'24, WearECG (ECG3to12)PLOS DH'25, ECGFlowCMRKDD'26 |
| Real-World Clinical Validation |
Opportunistic screening |
AVBI/LQTS, WPW, SVT, AF |
| RCTs |
Hyperkalemia, BNP, RVEFPulm Circ'25 |
| Special populations |
Pregnant WomenBMC MIDM'25 |
Working Experience
- 2024/09 - now, Assistant Professor (Assistant to the Dean since 2026/04), 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
Selected Publications
See full publications at
Google Scholar,
DBLP, and
PubMed
(*Corresponding author)
Top AI Medical Journal
[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)
Top AI Conference
[ICML 2026] Jiarui Jin, Haoyu Wang, Xingliang Wu, Xiaocheng Fang, Xiang Lan, Zihan Wang, Deyun Zhang, Bo Liu, Yingying Zhang, Xian Wu*, Hongyan Li*,
Shenda Hong*.
ECG-R1: Protocol-Guided and Modality-Agnostic MLLM for Reliable ECG Interpretation. ICML 2026
Team
Research Staff
- Deyun Zhang (2021-)
- Shijie Chen (2025-)
- Jianwei Chen (2026-)
PostDoc
Ph.D. Students
- Jun Li (2026-, RA since 2022)
- Xiaocheng Fang (2026-, co-supervise with Prof. Hongyan Li, RA since 2025)
- Jinshuai Gu (2026-, co-supervise with Prof. Yuxi Zhou)
- Mingke Yan (2025-)
- Jiarui Jin (2025-, co-supervise with Prof. Hongyan Li, RA since 2024)
- Guangkun Nie (2025-, co-supervise with Prof. Hongyan Li, RA since 2022)
- Shanwei Zhang (2025-, co-supervise with Prof. Yuxi Zhou)
- Donglin Xie (2024-)
- Yongfan Lai (2024-, co-supervise with Prof. Hongyan Li)
- Yongchao Long (2024-, co-supervise with Prof. Yuxi Zhou)
- Gongzheng Tang (2023-)
See Alumni page for former team members.