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个人简介 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余项。 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 Cybernetics, IF: 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 Systems, IF: 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 Systems, IF: 14.255 [4].  EaLDL: element-aware lifelong dictionary learning for multimode process monitoring,  IEEE Transactions on Neural Networks and Learning Systems, IF: 14.255 [5].   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 [6].  Cloud-edge collaborative method for industrial process monitoring based on error-triggered dictionary learning, IEEE Transactions on Industrial Informatics, IF: 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 applications, IEEE 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 Electronics, IF: 8.162 [13].  Detecting intelligent load redistribution attack based on power load pattern learning in cyber-physical power systems, IEEE Transactions on Industrial Electronics, IF: 8.162 [14].  Physical informed sparse learning for robust modeling of distributed parameter system and its industrial applications, IEEE Transactions on Automation Science and Engineering, IF:  6.636 [15].  Fault diagnosis of complex industrial systems based on multi-granularity dictionary learning and its application, IEEE Transactions on Automation Science and Engineering, IF:  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 network, Neural Networks, IF: 9.657 [21].  SDARE: A stacked denoising autoencoder method for game dynamics network structure reconstruction, Neural Networks, IF: 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, Engineering, IF: 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 Systems, IF: 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 process, Neurocomputing, IF: 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 Control, IF: 3.951 [40].  Distributed dictionary learning for high-dimensional process monitoring, Control Engineering Practice, IF: 4.057 [41].  Emergent inference of hidden markov models in spiking neural networks through winner-take-all, IEEE Transactions on Cybernetics, IF: 19.118 教育经历 [1]   2012.8-2017.4 清华大学  |  控制科学与工程  |  博士学位  |  博士研究生毕业 [2]   2008.8-2012.7 东北大学  |  自动化  |  学士学位  |  大学本科毕业 工作经历 [1]   2021.9-至今 中南大学  |  自动化学院  |  教授 [2]   2020.9-至今 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 社会兼职 [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 研究方向 [1]  复杂系统与复杂网络 [2]  大数据分析与处理 [3]  人工智能与机器学习 [4]  智能制造与工业互联网