✦个人简介
刘文涵，男，博士，讲师（内聘副教授），硕士生副导师，本科（2012~2016）、硕士（2016~2019）、博士（2021~2024）均毕业于武汉大学，2019~2021年于阿里巴巴集团担任算法工程师。主持省级科研项目2项，参与国家自然科学基金面上项目1项，在SCI期刊发表论文二十余篇，其中以一作身份发表13篇，担任若干SCI期刊审稿人，包括《Knowledge-based Systems》、《IEEE Journal of Biomedical and Health Informatics》、《Biomedical Signal Processing and Control》等。
✦研究方向
※人工智能
※心电信号处理
※物联网健康监护
※片上系统（SoC）
✦主要科研项目
※主持省级科研项目2项
※参与国家自然科学基金面上项目1项
✦论文成果
一作论文如下：(注：影响因子与分区以论文发表当时为准)：
[1] Liu Wenhan, Pan Shurong, Li Zhoutong, et al. Lead-fusion Barlow twins: A fused self-supervised learning method for multi-lead electrocardiograms[J]. Information Fusion, 2025, 114: 102698. (中科院1区TOP，影响因子14.800)
[2] Liu Wenhan, Guo Qianxi, Gao Xinwei, et al. Lead Separation and Combination: A Novel Unsupervised 12-Lead ECG Feature Learning Framework for Internet of Medical Things[J]. IEEE Internet of Things Journal, 2022, 9(23): 23897-23914. (中科院1区TOP，影响因子10.238)
[3] Liu Wenhan, Pan Shurong, Chang Sheng, et al. Direct Lead Assignment: A Simple and Scalable Contrastive Learning Method for ECG and Its IoMT Applications[J]. IEEE Internet of Things Journal, 2025, 12(5): 5672-5686.(中科院1区TOP，影响因子8.200)
[4] Liu Wenhan, Pan Shurong, Chang Sheng, et al. Self-Supervised Learning for Electrocardiogram Classification Using Lead Correlation and Decorrelation [J]. Applied Soft Computing, 2025, 172: 112871. (中科院1区TOP，影响因子7.200)
[5] Liu Wenhan, Zhang Huaicheng, Chang Sheng, et al. Learning Representations for Multilead Electrocardiograms From Morphology-Rhythm Contrast[J]. IEEE Transactions on Instrumentation and Measurement, 2024, 73: 1-15. (中科院2区TOP，影响因子5.600)
[6] Liu Wenhan, Li Zhoutong, Zhang Huaicheng, et al. Dense lead contrast for self-supervised representation learning of multilead electrocardiograms[J]. Information Sciences, 2023, 634: 189-205. (中科院1区TOP，影响因子8.100)
[7] Liu Wenhan, Pan Shurong, Li Zhoutong, et al. Bootstrap each lead’s latent: A novel method for self-supervised learning of multilead electrocardiograms[J]. Computer Methods and Programs in Biomedicine, 2024, 257: 108452. (中科院2区TOP，影响因子4.900)
[8] Liu Wenhan, Zhang Huaicheng, Chang Sheng, et al. A joint cross-dimensional contrastive learning framework for 12-lead ECGs and its heterogeneous deployment on SoC[J]. Computers in Biology and Medicine, 2023, 152: 106390. (中科院2区，影响因子6.698)
[9] Liu Wenhan, Wang Fei, Huang Qijun, et al. MFB-CBRNN: A Hybrid Network for MI Detection Using 12-Lead ECGs[J]. IEEE Journal of Biomedical and Health Informatics, 2020, 24(2): 503-514. (中科院2区，影响因子4.217)
[10] Liu Wenhan, Zhang Mengxin, Zhang Yidan, et al. Real-Time Multilead Convolutional Neural Network for Myocardial Infarction Detection[J]. IEEE Journal of Biomedical and Health Informatics, 2018, 22(5): 1434-1444. (中科院2区，影响因子3.850)
[11] Liu Wenhan, Guo Qianxi, Chen Siyun, Chang Sheng, Wang Hao, He Jin, Huang Qijun. A fully-mapped and energy-efficient FPGA accelerator for dual-function AI-based analysis of ECG[J]. Frontiers in Physiology, 2023, 14. (中科院2区TOP，影响因子4.755)
[12] Liu Wenhan, Ji Jiewei, Chang Sheng, et al. EvoMBN: Evolving Multi-Branch Networks on Myocardial Infarction Diagnosis Using 12-Lead Electrocardiograms[J]. Biosensors, 2022, 12(1),15. (中科院3区，影响因子5.519)
[13] Liu Wenhan, Huang Qijun, Chang Sheng, et al. Multiple-feature-branch convolutional neural network for myocardial infarction diagnosis using electrocardiogram[J]. Biomedical Signal Processing and Control, 2018, 45: 22-32.(中科院3区，影响因子2.943)
学术主页：
//scholar.google.com.hk/citations?hl=zh-CN&user=yE2BxnAAAAAJ&view_op=list_works&sortby=pubdate
✦联系方式
Email：[email protected]
