Language : English
黄科科
  • Personal Information

    Professor


    Supervisor of Doctorate Candidates


    Supervisor of Master's Candidates

    Date of Employment:2017-04-13

    School/Department:School of Automation

    Administrative Position:自动化学院副院长

    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:
    国家“万人计划”青年拔尖人才
    湖南省杰出青年基金
    IEEE TCSDM Young Professional Award
    全球前2%顶尖科学家榜单(World’s Top 2% Scientists 2023)
    中国科协青年托举人才
    湖湘青年英才
    湖湘青年科技创新人才
  • Profile

    黄科科,男,中南大学教授,博士生导师,硕士生导师,自动化学院副院长

    先后入选 国家“万人计划”青年拔尖人才、湖南省杰出青年基金、中国科协青年托举人才、湖湘青年英才、中南大学创新驱动青年人才。

    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。

    主持国家重点研发计划项目/课题、国家自然科学基金面上项目、青年基金、工信部工业互联网创新发展工程专项项目课题、中南大学创新驱动青年人才项目、校企合作重点项目等10项。

    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、全球前2%顶尖科学家榜单(World’s Top 2% Scientists 2023)等。在IEEE Trans.、IFAC会刊等国际期刊发表SCI论文80余篇,其中,8篇论文入选ESI热点/高被引学术论文。授权国内外发明专利20余项。

    担任IEEE Systems, Man, and Cybernetics Magazine、IET Cyber-Physical Systems、IEEE 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。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。


    招才引智:博士、硕士、本科生,欢迎联系。

    相关学科和研究领域包括但不限于:自动化、控制、计算机、数学、通信、工业互联网、人工智能、大数据分析等。

    课题组氛围融洽,经费充足,欢迎加入!


    代表性论文

    [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].  Error-triggered adaptive sparse identification for predictive control and its application to multiple operating conditions processes, IEEE Transactions on Neural Networks and Learning SystemsIF: 14.255

    [4].  EaLDL: element-aware lifelong dictionary learning for multimode process monitoring,  IEEE Transactions on Neural Networks and Learning SystemsIF: 14.255

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

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

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

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

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

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

    [11]. Knowledge-informed neural network for nonlinear model predictive control with industrial applicationsIEEE Transactions on Systems, Man, and Cybernetics: Systems, IF: 8.7 

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

    [13].  Detecting intelligent load redistribution attack based on power load pattern learning in cyber-physical power systems, IEEE Transactions on Industrial ElectronicsIF: 8.162

    [14].  Physical informed sparse learning for robust modeling of distributed parameter system and its industrial applications, IEEE Transactions on Automation Science and EngineeringIF:  6.636

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

    [16].  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

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

    [18].  Rotary kiln temperature control under multiple operating conditions: an error-triggered adaptive model predictive control solution,  IEEE Transactions on Control Systems Technology , IF:  5.418

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

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

    [21].  SDARE: A stacked denoising autoencoder method for game dynamics network structure reconstructionNeural NetworksIF: 9.657

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

    [23].  Multi-objective adaptive optimization model predictive control: decreasing carbon emissions from a zinc oxide rotary kiln, EngineeringIF: 12.834

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    [41].  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]   IEEE Systems, Man, and Cybernetics Magazine, Associate Editor
    [2]   IET Cyber-Physical Systems, Associate Editor
    [3]   IEEE TCCPS Newsletter, Associate Editor
    [4]   《中国有色金属学报(中英文版)》,青年编委
    [5]   《中南大学学报(自然科学版)》,青年编委
    [6]   中国有色金属学会自动化学术委员会,副秘书长
    [7]   中国自动化学会过程控制专业委员会,委员
    [8]   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
    [9]   中国自动化学会数据驱动控制学习与优化专委会,委员
    [10]   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

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