Language : English
黄科科
  • Personal Information

    Distinguished Associate Professor


    Supervisor of Doctorate Candidates


    Supervisor of Master's Candidates

    Date of Employment:2017-04-13

    School/Department:Automation

    Education Level:PhD Graduate

    Business Address:中南大学校本部民主楼215

    Sex:Male

    Contact Information:huangkeke@csu.edu.cn

    Degree:Doctoral degree

    Status:Employed

    Alma Mater:清华大学

    Discipline:Control Science and Engineering

    Honors and Titles:
    IEEE TCSDM Young Professional Award
    中国科协青年托举人才
    湖湘青年科技创新人才
  • Profile

    黄科科,男,中南大学特聘副教授,博士生导师,硕士生导师,人工智能系副主任、中国科协青年托举人才、中南大学创新驱动青年人才。

    2008年-2012年在东北大学自动化专业学习,获得工学学士学位。

    2012年-2017年在清华大学自动化系学习,获得工学博士学位。

    20174月起,进入中南大学信息科学与工程学院从事教学科研工作。

    主要研究方向包括:复杂系统与复杂网络;大数据分析与处理;人工智能与机器学习;智能制造与工业互联网

    主持和参与国家重点研发计划课题、国家自然科学基金面上/青年项目、工信部工业互联网创新发展工程、中南大学创新驱动计划项目、校企合作项目等10项。

    曾获中国自动化学会自然科学一等奖、IEEE TCSDM Young Professional Award等。在IEEE、IFAC汇刊等国际期刊发表SCI论文50余篇,其中,5篇论文入选ESI高被引学术论文,申请发明专利10余项。

    担任IET Cyber-Physical SystemsIEEE TCCPS Newsletter、《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。

    兼任中国自动化学会数据驱动控制学习与优化专委会委员、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、中国有色金属学会智能制造联盟秘书等。


    代表性论文

    [1].     Fault diagnosis of hydraulic systems based on deep learning model with multirate data samples, IEEE Transactions on Neural Networks and Learning Systems, IF: 10.451

    [2].     A projective and discriminative dictionary learning for high-dimensional process monitoring with industrial applications, IEEE Transactions on Industrial Informatics, IF: 10.215

    [3].     Static and dynamic joint analysis for operation condition division of industrial process with incremental learning, IEEE Internet of Things Journal, IF: 9.936

    [4].     Outlier detection for process monitoring in industrial cyber-physical systems, IEEE Transactions on Automation Science and Engineering, IF: 5.083

    [5].     SDARE: A stacked denoising autoencoder method for game dynamics network structure reconstruction, Neural Networks, IF: 8.05

    [6].     Robust structure identification of industrial cyber-physical system from sparse data: a network science perspective, IEEE Transactions on Automation Science and Engineering, IF: 5.083

    [7].     A geometry constrained dictionary learning method for industrial process monitoring, Information Sciences, IF: 6.795

    [8].     A robust transfer dictionary learning algorithm for industrial process monitoring, Engineering, IF: 7.553

    [9].     Reconstruction of tree network via evolutionary game data analysis, IEEE Transactions on Cybernetics, IF: 11.448

    [10].  Non-ferrous metals price forecasting based on variational mode decomposition and LSTM network, Knowledge-based SystemsIF: 8.038

    [11].  Adaptive process monitoring via online dictionary learning and its industrial application, ISA Transactions, IF: 5.468

    [12].  Structure dictionary learning-based multimode process monitoring and its application to aluminum electrolysis process, IEEE Transactions on Automation Science and Engineering, IF: 5.083

    [13].  Incorporating latent constraints to enhance inference of network structure, IEEE Transactions on Network Science and Engineering, IF: 5.213

    [14].  Multimode process monitoring based on robust dictionary learning with application to aluminium electrolysis processNeurocomputingIF: 5.719

    [15].  Distributed dictionary learning for industrial process monitoring with big data, Applied Intelligence, IF: 5.086

    [16].  Transfer dictionary learning method for cross-domain multimode process monitoring and fault isolation, IEEE Transactions on Instrumentation and Measurement, IF: 4.016

    [17].  Reweighted compressed sensing-based smart grids topology reconstruction with application to identification of power line outage, IEEE Systems Journal, IF: 3.931

    [18].  A multi-rate sampling data fusion method for fault diagnosis and its industrial applications, Journal of Process ControlIF: 3.666

    [19].  Distributed dictionary learning for high-dimensional process monitoringControl Engineering PracticeIF: 3.475

    [20].  Emergent inference of hidden markov models in spiking neural networks through winner-take-all, IEEE Transactions on CyberneticsIF: 11.448

  • Research Field

  • Social Affiliations

    [1]    IET Cyber-Physical Systems, Associate Editor
    [2]   IEEE TCCPS Newsletter, Associate Editor
    [3]   《中南大学学报(自然科学版)》,青年编委
    [4]   中国自动化学会数据驱动控制学习与优化专委会,委员
    [5]   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
    [6]   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

    Sorry, no related content currently!
  • Research Group

    No content
  • Other Contact Information

     Zip Code:
     Postal Address:
     Mobile:
     Email: