Shenda HongPhD

Assistant Professor, National Institute of Health Data Science, Peking University

Contact Info

No.38 Xueyuan Rd.; Haidian District; Beijing; China. 100091


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

SPJ Health Data Science, Associate Editor

Major Awards and Honors

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

National Scholarship, 2017/12 and 2013/10

Narrative Report of Research Contributions

His research interests are data mining and artificial intelligence for real-world healthcare data, especially deep learning for temporal medical data–such as temporal events, time series (e.g. longitudinal data, electronic health records, claims data), and physiological signals (e.g. electrocardiogram, electroencephalogram, polysomnogram, heart rates). He serves as a program committee member or reviewer for international conferences including KDD, ICLR, NeurIPS, ICML, AAAI and IJCAI. He also led a team that won the first place of the 18th PhysioNet/Computing in Cardiology Challenge.

We are recruiting self-motivated Ph.D. and interns who have a strong passion for health data science with coding skills. If you are interested, please send email with your CV.


(# equal contributions, * corresponding author)


[BSPC 2023] Wenrui Zhang, Shijia Geng, Shenda Hong*. A Simple Self-Supervised ECG Representation Learning Method via Manipulated Temporal-Spatial Reverse Detection. Biomedical Signal Processing and Control79(2023): 104194(IF=5.076, JCR Q2)


[ICML 2022] Ling Yang, Shenda Hong*. Unsupervised Time-Series Representation Learning with Iterative Bilinear Temporal-Spectral Fusion. International Conference on Machine Learning (ICML) 2022, 25038-25054. Acceptance rate 21.9% (1235/5630). (CCF-A)

[ICML 2022] Ling Yang, Shenda Hong*. Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning. International Conference on Machine Learning (ICML) 2022, 25022-25037. Acceptance rate 21.9% (1235/5630). (CCF-A)

[AAAI 2022] Xiang Lan, Dianwen Ng, Shenda Hong*, Mengling Feng*. Intra-Inter Subject Self-Supervised Learning for Multivariate Cardiac Signals. AAAI Conference on Artificial Intelligence (AAAI) 2022, 4532-4540. Acceptance rate 15.0% (1349/9020). (CCF-A)