2017.09-2023.03，上海交通大學(xué)，機(jī)械工程，博士

2013.09-2017.06，四川大學(xué)，機(jī)械設(shè)計(jì)制造及其自動(dòng)化，學(xué)士

2025.03 至今，上海交通大學(xué)，機(jī)械與動(dòng)力工程學(xué)院，助理教授

2023.03-2025.02，上海交通大學(xué)，機(jī)械與動(dòng)力工程學(xué)院，博士后

1、人工智能/大模型在醫(yī)學(xué)中交叉

2、機(jī)器健康與智能運(yùn)維

團(tuán)隊(duì)致力于探索端-邊-云聯(lián)動(dòng)的多模態(tài)信息智能感知及基于大模型的智能分析方法，實(shí)現(xiàn)各類機(jī)器人在非受控環(huán)境下（醫(yī)療、工業(yè)等應(yīng)用場(chǎng)景）的智能決策。

團(tuán)隊(duì)歡迎有興趣的本科、碩士及博士同學(xué)加入課題組，一起解決人工智能交叉領(lǐng)域的前沿挑戰(zhàn)。

Editorial board：
[1] Scientific Reports, Youth Editorial board member 青年編委

[2] iMeta (IF=33.2), Youth Editorial board member 青年編委

[3] Science合作期刊Biomedical Engineering Frontiers, Youth Editorial board member 青年編委

Reviewers：

IEEE Journal of Biomedical and Health Informatics, Knowledge-Based Systems, Engineering Applications of Artificial Intelligence, IEEE Transactions on Instrumentation and Measurement, Neurocomputing, Biomedical Signal Processing and Control, Applied Intelligence等期刊審稿人

[1] 國(guó)家自然科學(xué)基金青年項(xiàng)目:面向多源場(chǎng)景的致死性心律失常異構(gòu)特征建模及早期預(yù)測(cè)研究，項(xiàng)目負(fù)責(zé)人，2025-2027

[2] 全國(guó)博士后創(chuàng)新人才支持計(jì)劃:心律失常增量自更新智能診斷及惡性事件早期預(yù)警機(jī)理研究，項(xiàng)目負(fù)責(zé)人，2023-2025

[3] 中國(guó)博士后科學(xué)基金面上項(xiàng)目:融合專家知識(shí)的心電信號(hào)質(zhì)量建模及智能診斷方法研究，項(xiàng)目負(fù)責(zé)人，2023-2025

[4] 國(guó)家自然科學(xué)基金面上項(xiàng)目: 高壓高速微型柱塞泵服役性能退化機(jī)理與健康評(píng)估預(yù)測(cè)方法，項(xiàng)目參與人，2025-2028

[5] 上海交通大學(xué)“交大之星”計(jì)劃醫(yī)工交叉研究基金項(xiàng)目:基于消化內(nèi)鏡下共聚焦圖像的AI輔助早期胃癌實(shí)時(shí)診斷系統(tǒng)研發(fā)，項(xiàng)目參與人，2024-2026

[6] 國(guó)家重點(diǎn)研發(fā)計(jì)劃:基于云平臺(tái)的便攜式老人健康監(jiān)測(cè)系統(tǒng)與應(yīng)用示范，項(xiàng)目參與人，2019-2022

[7] 上海市衛(wèi)健委智慧醫(yī)療專項(xiàng)研究項(xiàng)目:基于人工智能的心律失常監(jiān)測(cè)與大數(shù)據(jù)分析，項(xiàng)目參與人，2018-2021

在npj digital medicine (Nature子刊, IF=15.1) , Cell Reports Medicine (Cell子刊, IF=10.6), information fusion (中科院一區(qū)Top, IF=15.5)等國(guó)內(nèi)外權(quán)威期刊上發(fā)表SCI論文46篇

[1] Wei X., Li Z., Tian Y., Wang M., Jin Y.*, Ding W., Liu C. Spatial-temporal hierarchical decoupled masked autoencoder: A self-supervised learning framework for electrocardiogram. Expert Systems with Applications, 2026, 298: 129603. (中科院1區(qū)Top)

[2] Jin Y., Wang M., Li Z., et al. Unsupervised artificial intelligence model of arrhythmia diagnosis: Improving model performance on different ECG datasets. Biomedical Signal Processing and Control, 2026, 112: 108693. (中科院2區(qū))

[3] Chen T., Wen J., Shen X., Shen J., Deng J., Zhao M., Xu L., Wu C., Yu B., Yang M., Ma M., Wu J., She Y., Zhong Y., Hou L., Jin Y.*, Chen C. Whole slide image based deep learning refines prognosis and therapeutic response evaluation in lung adenocarcinoma. npj Digital Medicine, 2025, 8(1): 69. (Nature子刊)

[4] Wang M., Li Z., Tian Y., Wei X., Jin Y.*, Liu C. BioCross: A cross-modal framework for unified representation of multi-modal biosignals with heterogeneous metadata fusion. Information Fusion, 2025, 123: 103302. (中科院1區(qū)Top)

[5] Li Z., Tian Y., Jin Y.*, et al. An early warning method for arrhythmias in long-term ECGs based on self-supervised learning and LSTM. Knowledge-Based Systems, 2025, 327(9): 114137. (中科院1區(qū)Top)

[6] Wang M., Tian Y., Li Z., Wei X., Jin Y.*, Liu C., Zhao L. Multi-task learning for multi-label electrocardiogram disease detection via point-level delineation-guided fusion. Engineering Applications of Artificial Intelligence, 2025, 160: 111894. (中科院1區(qū)Top)

[7] Li Z., Tian Y., Jin Y.*, et al. EDDM: A Novel ECG Denoising Method Using Dual-path Diffusion Model. IEEE Transactions on Instrumentation and Measurement, 2025, 74: 2509815. (中科院2區(qū))

[8] Jin Y., Li Z., Wang M., et al. Cardiologist-level interpretable knowledge-fused deep neural network for automatic arrhythmia diagnosis, Communications Medicine, 2024, 4: 31. (Nature系列期刊)

[9] Jin Y., Li Z., Tian Y., et al. A self-supervised framework for computer-aided arrhythmia diagnosis, Applied Soft Computing, 2024, 164: 112024. (中科院2區(qū)Top)

[10] Jin Y., Li Z., Tian Y., et al. A novel interpretable multilevel wavelet decomposition deep network for actual heartbeat classification, Science China Technological Sciences, 2024, 67(6): 1842-1854. (中科院1區(qū)Top)

[11] Jin Y., Qin C., Liu J., et al. A novel deep wavelet convolutional neural network for actual ECG signal denoising, Communications Medicine, Biomedical Signal Processing and Control, 2024, 87: 105480. (中科院2區(qū))

[12] Wei X., Li Z., Tian Y., Wang M., Liu J., Jin Y.*, Ding W. *, Liu C*. Differentiated knowledge distillation: Patient-specific single-sample personalization for electrocardiogram diagnostic models. Engineering Applications of Artificial Intelligence, 2024, 136: 108880. (中科院1區(qū)Top)

[13] Li Z., Jin Y.*, Tian Y., et al M-XAF: Medical explainable diagnosis system of atrial fibrillation based on medical knowledge and semantic representation fusion. Engineering Applications of Artificial Intelligence, 2024, 136: 108890. (中科院1區(qū)Top)

[14] Qin C.*, Jin Y.*, Zhang Z., et al. Anti-noise diesel engine misfire diagnosis using a multi-scale CNN-LSTM neural network with denoising module. CAAI Transactions on Intelligence Technology, 2023. (中科院1區(qū)Top, ESI高被引論文)

[15] Jin Y., Li Z., Qin C., et al. A novel attentional deep neural network-based assessment method for ECG quality. Biomedical Signal Processing and Control, 2023, 79: 104064. (中科院2區(qū), ESI高被引論文)

[16] Jin Y., Qin C., Tao J., et al. An accurate and adaptative cutterhead torque prediction method for shield tunneling machines via adaptative residual long-short term memory network. Mechanical Systems and Signal Processing, 2022, 165: 108312. (中科院1區(qū)Top)

[17] Jin Y., Liu J., Liu Y., et al. A Novel Interpretable Method Based on Dual-Level Attentional Deep Neural Network for Actual Multilabel Arrhythmia Detection. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 2500311. (中科院2區(qū))

[18] Jin Y., Li Z., Liu Y., et al. Multi-class 12-lead ECG automatic diagnosis based on a novel subdomain adaptive deep network. Science China Technological Sciences, 2022, 65(11): 2617–2630. (中科院1區(qū)Top)

[19] Jin Y., Qin C., Zhang Z., et al. A multi-scale convolutional neural network for bearing compound fault diagnosis under various noise conditions. Science China Technological Sciences, 2022, 65. (中科院1區(qū)Top, 中國(guó)科學(xué)2023年度優(yōu)秀論文)

[20] Jin Y., Qin C., Liu J., et al. A Novel Incremental and Interactive Method for Actual Heartbeat Classification with Limited Additional Labeled Samples. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 9387357. (中科院2區(qū))

[21] Jin Y., Qin C., Huang Y., et al. Actual bearing compound fault diagnosis based on active learning and decoupling attentional residual network. Measurement, 2021, 173: 108500. (中科院2區(qū)Top, ESI高被引論文)

[22] Jin Y., Feng Q., Zhang X., et al. Deep domain adversarial residual neural network for sustainable wind turbine cyber-physical system fault diagnosis. Software - Practice and Experience, 2021, 51 (11): 2128-2142.

[23] Jin Y., Qin C., Huang Y., et al. Multi-domain modeling of atrial fibrillation detection with twin attentional convolutional long short-term memory neural networks. Knowledge-Based Systems, 2020, 193: 105460. (中科院1區(qū)Top)

[24] Jin Y., Qin C., Liu J., et al. A novel Domain Adaptive Residual Network for automatic Atrial Fibrillation Detection. Knowledge-Based Systems, 2020, 203: 106122. (中科院1區(qū)Top)

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