Language : English
  • Personal Information


    Supervisor of Doctorate Candidates

    Supervisor of Master's Candidates

    Date of Employment:2017-04-13


    Administrative Position:人工智能系副主任

    Education Level:PhD Graduate

    Business Address:中南大学校本部民主楼215



    Degree:Doctoral degree


    Alma Mater:清华大学

    Discipline:Control Science and Engineering

    Honors and Titles:
    IEEE TCSDM Young Professional Award
  • Profile





    曾获中国自动化学会自然科学一等奖、中国有色金属工业科技进步一等奖、IEEE TCSDM Young Professional Award等。在IEEEIFAC汇刊等国际期刊发表SCI论文80余篇,其中,5篇论文入选ESI高被引学术论文,授权发明专利10余项。

    担任IET Cyber-Physical SystemsIEEE TCCPS Newsletter、《中国有色金属学报(中英文版)》、《中南大学学报(自然科学版)》等多个国内外期刊编委和审稿人。兼任中国有色金属学会自动化学术委员会副秘书长、中国自动化学会过程控制专业委员会委员、中国自动化学会技术过程的故障诊断与安全性专委会委员、中国自动化学会青年工作委员会委员、中国自动化学会数据驱动控制学习与优化专委会委员、中国有色金属学会智能制造联盟秘书、中国图学学会数字孪生专业委员会委员、信息技术新工科产学研联盟工业互联网工作委员会委员等。


    [1].  Adaptive multimode process monitoring based on mode-matching and similarity-preserving dictionary learning, IEEE Transactions on CyberneticsIF: 19.118

    [2].  Metric learning based fault diagnosis and anomaly detection for industrial data with intra-class variance, IEEE Transactions on Neural Networks and Learning SystemsIF: 14.255

    [3].  Fault diagnosis of hydraulic systems based on deep learning model with multirate data samples,  IEEE Transactions on Neural Networks and Learning Systems, IF: 14.255

    [4].  Cloud-edge collaborative method for industrial process monitoring based on error-triggered dictionary learning, IEEE Transactions on Industrial InformaticsIF: 11.648

    [5].  Trustworthiness of process monitoring in IIoT based on self-weighted dictionary learning, IEEE Transactions on Industrial Informatics, IF: 11.648

    [6].  A projective and discriminative dictionary learning for high-dimensional process monitoring with industrial applications, IEEE Transactions on Industrial Informatics, IF: 11.648

    [7].  Static and dynamic joint analysis for operation condition division of industrial process with incremental learning, IEEE Internet of Things Journal, IF: 10.238

    [8].  A systematic procurement supply chain optimization technique based on industrial internet of thing and application, IEEE Internet of Things Journal, IF: 10.238

    [9].  LSTM-MPC: A deep learning based predictive control method for multimode process control, IEEE Transactions on Industrial ElectronicsIF: 8.162

    [10].  Outlier detection for process monitoring in industrial cyber-physical systems, IEEE Transactions on Automation Science and Engineering, IF: 6.636

    [11].  LSTMED: An uneven dynamic process monitoring method based on LSTM and Autoencoder neural networkNeural NetworksIF: 9.657

    [12].  SDARE: A stacked denoising autoencoder method for game dynamics network structure reconstruction, Neural Networks, IF: 9.657

    [13].  Fault diagnosis of complex industrial systems based on multi-granularity dictionary learning and its application, IEEE Transactions on Automation Science and EngineeringIF:  6.636

    [14].  Robust structure identification of industrial cyber-physical system from sparse data: a network science perspective, IEEE Transactions on Automation Science and Engineering, IF:  6.636

    [15].  Nonstationary industrial process monitoring based on stationary projective dictionary learning,  IEEE Transactions on Control Systems Technology , IF:  5.418

    [16].  A geometry constrained dictionary learning method for industrial process monitoring, Information Sciences, IF: 8.233

    [17].  A robust transfer dictionary learning algorithm for industrial process monitoring, Engineering, IF: 12.834

    [18].  Reconstruction of tree network via evolutionary game data analysis, IEEE Transactions on Cybernetics, IF: 19.118

    [19].  Non-ferrous metals price forecasting based on variational mode decomposition and LSTM network, Knowledge-based SystemsIF: 8.139

    [20].  Adaptive process monitoring via online dictionary learning and its industrial application, ISA Transactions, IF: 5.911

    [21].  A latent feature oriented dictionary learning method for closed-loop process monitoring, ISA Transactions, IF: 5.911

    [22].  Structure dictionary learning-based multimode process monitoring and its application to aluminum electrolysis process, IEEE Transactions on Automation Science and Engineering, IF: 6.636

    [23].  Incorporating latent constraints to enhance inference of network structure, IEEE Transactions on Network Science and Engineering, IF: 5.033

    [24].  Intrusion detection of industrial internet-of-things based on reconstructed graph neural networks, IEEE Transactions on Network Science and Engineering, IF: 5.033

    [25].  Multimode process monitoring based on robust dictionary learning with application to aluminium electrolysis processNeurocomputingIF: 5.779

    [26].  Distributed dictionary learning for industrial process monitoring with big data, Applied Intelligence, IF: 5.019

    [27].  Label propagation dictionary learning based process monitoring method for industrial process with between-mode similarity, Science China Information Sciences, IF: 7.275

    [28].  Ensemble forecasting for product futures prices using variational mode decomposition and artificial neural networks, Chaos Solitons and Fractals, IF: 9.922

    [29].  Transfer dictionary learning method for cross-domain multimode process monitoring and fault isolation, IEEE Transactions on Instrumentation and Measurement, IF: 5.332

    [30].  Unified stationary and nonstationary data representation for process monitoring in IIoT , IEEE Transactions on Instrumentation and Measurement, IF: 5.332

    [31].  Reweighted compressed sensing-based smart grids topology reconstruction with application to identification of power line outage, IEEE Systems Journal, IF: 4.902

    [32].  A multi-rate sampling data fusion method for fault diagnosis and its industrial applications, Journal of Process ControlIF: 3.951

    [33].  Distributed dictionary learning for high-dimensional process monitoringControl Engineering PracticeIF: 4.057

    [34].  Emergent inference of hidden markov models in spiking neural networks through winner-take-all, IEEE Transactions on CyberneticsIF: 19.118

  • Research Field

  • Social Affiliations

    [1]    IET Cyber-Physical Systems, Associate Editor
    [2]   IEEE TCCPS Newsletter, Associate Editor
    [3]   《中国有色金属学报(中英文版)》,青年编委
    [4]   《中南大学学报(自然科学版)》,青年编委
    [5]   中国有色金属学会自动化学术委员会,副秘书长
    [6]   中国自动化学会过程控制专业委员会,委员
    [7]   中国自动化学会技术过程的故障诊断与安全性专委会,委员
    [8]   中国自动化学会数据驱动控制学习与优化专委会,委员
    [9]   中国自动化学会青年工作委员会,委员
  • Education Background

    [1]  2012.8- 2017.4
    清华大学 | 控制科学与工程 | PhD Graduate | Doctoral degree
    [2]  2008.8- 2012.7
    东北大学 | 自动化 | University graduated | Bachelor's degree
  • Work Experience

    [1]  2021.9- Now
    中南大学 | 自动化学院 | 教授
    [2]  2020.9- Now
    中南大学 | 自动化学院 | 博士生导师
    [3]  2017.4- 2021.9
    中南大学 | 自动化学院 | 特聘副教授
  • Research Group

    No content
  • Other Contact Information

     Zip Code:
     Postal Address: