欢迎来到北京大学健康医疗大数据国家研究院

设为首页 | 加入收藏
洪申达
时间:2022-10-04 15:31:54来源: 点击数:


undefined   洪申达

   职称:助理教授、副研究员                  

    办公地点:北京大学医学部医学科技楼西楼5层

    邮箱hongshenda@pku.edu.cn


个人简介


北京大学健康医疗大数据国家研究院助理教授、副研究员、博士生导师,研究方向为电子病历、生理信号等医疗时序数据的人工智能算法研究及临床应用。目前主持国家自然科学基金青年科学基金项目1项,在TPAMITKDEKDDWWWICMLAAAIIJCAI等会议期刊上发表论文50余篇,其中第一/通讯作者(含共同)论文30余篇。担任SPJ Health Data Science期刊Associate Editor,担任KDDICLRICMLNeurIPSThe Lancet Digital HealthNPJ Digital Medicine等国际会议和期刊的PC Member或审稿人。曾获得PhysioNet Challenge 2017 First Place、第五届中国"互联网+"大学生创新创业大赛全国金奖等,相关产品已取得医疗器械注册证。个人主页 https://hsd1503.github.io/


2022/08-今,北京大学 健康医疗大数据国家研究院,助理教授/副研究员/博士生导师

2020/09-2022/07,北京大学 健康医疗大数据国家研究院,博雅博士后/助理研究员

2019/09-2020/08,佐治亚理工学院 计算科学与工程学院、哈佛医学院 麻省总医院,博士后

2014/09-2019/06,北京大学 信息科学技术学院 智能科学系,理学博士

2010/09-2014/06,北京邮电大学 理学院 数学系,理学学士


主要研究方向


电子病历、生理信号等医疗时序数据的人工智能算法研究及临床应用


undefined代表性科研项目


2022-2024,主持,国家自然科学基金青年项目

                     健康医疗时序数据上结合人工特征和深度神经网络的算法研究


undefined代表性论文


1. [AJH 2022] Xiao-Dong Mo#, Shen-Da Hong#, Yan-Li Zhao, Er-Lie Jiang, Jing Chen, Yang Xu, Zi-Min Sun, Wei-Jie Zhang, Qi-Fa Liu, Dai-Hong Liu, Ding-Ming Wan, Wen-Jian Mo, Han-Yun Ren, Ting Yang, He Huang, Xi Zhang, Xiao-Ning Wang, Xian-Min Song, Su-Jun Gao, Xin Wang, Yi Chen, Bing Xu, Ming Jiang, Xiao-Bing Huang, Xin Li, Hong-Yu Zhang, Hong-Tao Wang, Zhao Wang, Ting Niu, Ji-Shi Wang, Ling-Hui Xia, Xiao-Dan Liu, Fei Li, Fang Zhou, Tao Lang, Jiong Hu, Sui-Jing Wu, Xiao-Jun Huang. Basiliximab for Steroid-refractory Acute Graft-versus-host Disease: A Real-world Analysis. American Journal of Hematology 2022 Apr;97(4):458-469.

2. [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)

3. [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)

4.[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)

5. [IJCAI 2022] Derun Cai, Moxian Song, Chenxi Sun, Baofeng Zhang, Shenda Hong*, Hongyan Li*. Hypergraph Structure Learning for Hypergraph Neural Networks. In Proceedings of the 31th International Joint Conference on Artificial Intelligence, IJCAI 2022, 1923-1929. Acceptance rate 14.9% (679/4535). (CCF-A)

6. [WWW 2020] Shenda Hong, Zhaoji Fu, Rongbo Zhou, Jie Yu, Yongkui Li, Kai Wang, Guanlin Cheng. CardioLearn: A Cloud Deep Learning Service for Cardiac Disease Detection from Electrocardiogram. In the Web Conference (WWW) 2020, 148-152.

7. [KDD 2020] Shenda Hong#, Yanbo Xu#, Alind Khare#, Satria Priambada#, Kevin Maher, Alaa Aljiffry, Jimeng Sun, Alexey Tumanov. HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2020, 1614-1624. Acceptance rate 16.9% (216/1279). (CCF-A)

8. [IJCAI 2019] Shenda Hong, Cao Xiao, Tengfei Ma, Hongyan Li, Jimeng Sun. MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, pages 5888-5894, 2019. Acceptance rate 17.9% (850/4752). (CCF-A)

9. [IJCAI 2019] Shenda Hong, Cao Xiao, Trong Nghia Hoang, Tengfei Ma, Hongyan Li, Jimeng Sun. RDPD: Rich Data Helps Poor Data via Imitation. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, pages 5895-5901, 2019. Acceptance rate 17.9% (850/4752). (CCF-A)

10. [PMEA 2019] Shenda Hong, Yuxi Zhou, Meng Wu, Junyuan Shang, Qingyun Wang, Hongyan Li, Junqing Xie. Combining Deep Neural Networks and Engineered Features for Cardiac Arrhythmia Detection from ECG Recordings. Physiological Measurement, 40(5):054009, 2019. (IOP Publishing 2021 Top 1% Cited Paper Award)


本课题组招收科研助理、博士生,与北京大学智能学院、医学部附属医院、可穿戴及医疗设备厂商等有密切合作,有意者请将个人简历发至hongshenda@pku.edu.cn



 



北京大学健康医疗大数据国家研究院版权所有 2019-2020