刘若楠，博士生导师，德国洪堡学者，中国科协青年托举人才

目前课题组经费非常充足，欢迎自动化、计算机、机械工程以及其他相关专业的同学Email简历来实验室开展本科、硕士、博士研究工作。

2024.05至今  上海交通大学 自动化系  长聘教轨副教授 

2019 - 2024  天津大学 人工智能学院  长聘/英才副教授

2017 - 2019  卡耐基梅隆大学 计算机科学学院 联合培养博士/博士后研究员 

2009 - 2019  西安交通大学 机械工程 本硕博连读

机器学习、深度学习

智能动态无人系统感知与融合

高端装备智能运维、故障诊断与寿命预测等

主持 国自然青年项目 小样本下动态图网络的鲁棒学习研究

主持 天津市应用基础研究项目 知识与数据联合驱动的可解释图神经网络研究

主持 CCF-百度松果基金 融合知识的图神经网络计算研究

主持 青年人才托举工程 机器学习

主持 国防基础科研计划重点项目课题 XX系统XX定位、诊断与预测

主持 自主创新基金 开放环境增量学习的分层建模方法研究

主持 自主创新基金 深海装备动力系统的多粒度故障诊断研究

参与 973项目“航空发动机运行安全基础研究”

参与 Deep Intermodal Video Analytics (DIVA) Program (Supported by IARPA via DOI/IBC Department Contract number D17PC00340)

德国洪堡学者

中国科协青年托举人才

全球前2%顶尖科学家（World's Top 2% Scientists）（2021年-至今连续三年）

《IEEE Transactions on Industrial Cyber-Physical Systems》、《Sustainable Energy Technologies and Assessments》、《Frontiers in Artificial Intelligence》等期刊首席客座编委/编委

IEEE工业电子学会技术委员会成员

The 31st IEEE International Symposium on Industrial Electronics (ISIE 2022)分会主席

2021年度智能感知领域排名第一、IEEE工业信息学汇刊IEEE Trans. on Industrial Informatics最佳论文奖（IF 12.3）

[23] Liu R, Zhang Q, Han T*, et al. Survey on Foundation Models for Prognostics and Health Management in Industrial Cyber-Physical Systems[J]. IEEE Transactions on Industrial Cyber-Physical Systems, 2024.

[22] Liu R, Zhang Q, Lin D*, et al. Causal intervention graph neural network for fault diagnosis of complex industrial processes[J]. Reliability Engineering & System Safety, 2024.

[21]Cheng P, Ye S,  Liu R, et al. SMC-Based Bounded Consensus Tracking for Multiagent Systems Under Stochastic DoS Attacks With Applications to Multiple DC Motors[J]. IEEE Transactions on Industrial Informatics, 2024.

[20] Liu R, Xiao D, Lin D*, et al. Intelligent Bearing Anomaly Detection for Industrial Internet of Things Based on Auto-Encoder Wasserstein Generative Adversarial Network[J]. IEEE Internet of Things Journal, 2024.

[19] Liu R, Zhang Q, Wang Y*, et al. Industrial Big Data Analytical System in Industrial Cyber-Physical Systems Based on Coarse-to-Fine Deep Network[J]. IEEE Transactions on Industrial Cyber-Physical Systems, 2023.      

[18] Wang H, Liu R*, Ding S X, et al. Causal-Trivial Attention Graph Neural Network for Fault Diagnosis of Complex Industrial Processes[J]. IEEE Transactions on Industrial Informatics, 2023.

[17] Lin D, Wang X, Shen J, Zhang R, Liu R, et al. Generative Status Estimation and Information Decoupling for Image Rain Removal[C] //Advances in Neural Information Processing Systems (NeurIPS 2022).

[16] Chen D, Liu R*, Hu Q, et al. Interaction-Aware Graph Neural Networks for Fault Diagnosis of Complex Industrial Processes[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021. (ESI, Hot Paper) [link]

[15] Chen H, Liu R*, Xie Z, et al. Majorities Help Minorities: Hierarchical Structure Guided Transfer Learning for Few-shot Fault Recognition[J]. Pattern Recognition, 2021: 108383[link]

[14] Hu Y, Liu R*, Li X, et al. Task-Sequencing Meta Learning for Intelligent Few-Shot Fault Diagnosis with Limited Data[J]. IEEE Transactions on Industrial Informatics, 2021.[link]

[13]Wang Y, Liu R*, Lin D, et al, Coarse-to-Fine: Progressive Knowledge Transfer Based Multi-Task Convolutional Neural Network for Intelligent Large-Scale Fault Diagnosis[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021. [link]

[12] Wang F, Liu R*, Hu Q, et al. Cascade convolutional neural network with progressive optimization for motor fault diagnosis under nonstationary conditions[J]. IEEE Transactions on Industrial Informatics, 2020, 17(4): 2511-2521[link]

[11] Liu R, Wang F, Yang B*, et al. Multi-scale Kernel based Residual Convolutional Neural Network for Motor Fault Diagnosis Under Non-stationary Conditions[J]. IEEE Transactions on Industrial Informatics, 2019. (ESI) [link]

[10] Yang B, Liu R*, Zio E. Remaining useful life prediction based on a double-convolutional neural network architecture[J]. IEEE Transactions on Industrial Electronics, 2019, 66(12): 9521-9530. (ESI) [link]

[9]Liu R, Yang B*, Hauptmann A G. Simultaneous Bearing Fault Recognition and Remaining Useful Life Prediction Using Joint-Loss Convolutional Neural Network[J]. IEEE Transactions on Industrial Informatics, 2019, 16(1): 87-96. (ESI, 2021 Outstanding Paper Award in IEEE TII)[link]

[8] Liu R, Yang B, Zio E, et al. Artificial intelligence for fault diagnosis of rotating machinery: A review[J]. Mechanical Systems and Signal Processing, 2018, 108: 33-47. (ESI, Hot Paper) [link]

[7] Liu R, Meng G, Yang B, et al. Dislocated time series convolutional neural architecture: An intelligent fault diagnosis approach for electric machine[J]. IEEE Transactions on Industrial Informatics, 2016, 13(3): 1310-1320. (ESI) [link]

[6] Liu R, Yang B, Zhang X, et al. Time-frequency atoms-driven support vector machine method for bearings incipient fault diagnosis[J]. Mechanical Systems and Signal Processing, 2016, 75: 345-370. (ESI)[link]

[5] Yang B,Liu R, Chen X. Sparse Time-Frequency Representation for Incipient Fault Diagnosis of Wind Turbine Drive Train [J]. IEEE Transactions on Instrumentation and Measurement, 2018. [link]

[4] Yang B,Liu R, Chen X. Fault Diagnosis for Wind Turbine Generator Bearing via Sparse Representation and Shift-invariant K-SVD [J]. IEEE transactions on Industrial Informatics, 2016. [link]

[3] Chen D, Liu R*, Yu W, et al. Fault Diagnosis of Industrial Control System With Graph Attention Network on Multi-view Graph[C]//2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT). IEEE, 2021: 617-623. [link]

[2] Zhang K,Liu R*, Chen D, et al. Synthesize Missing Modality Based on Latent Space Model[C]//2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT). IEEE, 2021: 557-563.[link]

[1] Pu Y, Liu R*, Chen Q, et al. POC: Periodical Orthogonal Center Loss For Open Set Classification[C]//2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT). IEEE, 2021: 433-43[link]