Shenda Hong
洪申达
Avatar of Shenda Hong
Assistant Professor
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

Recruitment Announcement [2026/02]

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
  • Ph.D. One position available at School of Intelligence Science Technology (2027 Fall), one position available at National Institute of Health Data Science (2027 Fall)
  • Research Assistant with proficient coding skills

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 and biosignals (e.g., ECG, PPG, EEG, PSG, PCG, 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

  • Biosignal Specialized MLLMs: Constructing domain-specific multimodal large language models, such as ECG-R1, GEM, and SpiroLLM, to bridge the semantic gap between time-series biosignals and clinical language.
  • Biosignal Foundation Models: Developing generalist foundation models, such as ECGFounder, SleepFounder, AnyECG, AnyPPG, by leveraging large-scale, multi-modality databases to enable robust representation learning and zero-shot generalization across diverse clinical tasks.
  • Digital Biomarker Discovery: Establishing a systematic paradigm, such as Sleep Depth Index, PPGage, ECGomics, to transform high-dimensional biosignals into structured, quantifiable metrics.
  • AI for Digital Health: Enhancing smart devices with AI, including Portable ECG Device, Flexible ECG Patch, ECG Pad, smart ring (with PPG sensor), smart stethoscope (with PCG sensor), smart cap (with EEG sensor).
  • Real-World Clinical Validation: Conducting rigorous real-world studies, including opportunistic screening systems for AVBI/LQTS, WPW, SVT, AF, and randomized controlled trials (RCTs), to evaluate the clinical efficacy and implementation pathways of AI-ECG interventions.

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

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)
[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)
[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

Top AI Conference

[ICLR 2026] Yongchao Long, Yingying Zhang, Xianbin Wen, Xian Wu*, Yuxi Zhou*, Shenda Hong*. Copy-Paste to Mitigate Large Language Model Hallucinations. ICLR 2026
[NeurIPS 2025] Xiang Lan, Feng Wu, Kai He, Qinghao Zhao, Shenda Hong*, Mengling Feng*. GEM: Empowering MLLM for Grounded ECG Understanding with Time Series and Images. NeurIPS 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. ICLR 2025
[ICLR 2025] Guangkun Nie, Gongzheng Tang, Shenda Hong*. Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint. 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. ICLR 2024

Teaching

  • Basis of Python Programming in Health Data Science (for undergraduate students, graduate students and Continuing Education in Medicine)

Awards

Grants

  • CCF-Tencent Rhino-Bird Open Research Fund, 2025
  • CCF-Zhipu Large Model Innovation Fund, 2024
  • PKU-OPPO Fund, 2023/2025
  • National Natural Science Foundation of China, 2022

Services

  • Associate Editor of npj Digital Medicine, SPJ Health Data Science
  • Journal Reviewer of NEJM AI, Lancet Digital Health, EHJ Digital Health, and many others
  • Conference Reviewer of ICLR, ICML, NeurIPS, KDD, AAAI, IJCAI
  • External Reviewer of Center for Medical Device Evaluation (National Medical Products Administration, NMPA) of China

Team

Research Staff

PostDoc

  • Cheng Zhang (2026-)

Ph.D. Students

See Alumni page for former team members.

Last update: 2026/02/13