金军委，男，1989.06月生，博士，讲师。
电子邮箱：jinjunwei24@163.com.
研究方向：机器学习、模式识别、计算机视觉.
教育经历：
2009.09-2013.06,宁夏大学,数学与应用数学专业,学士;
2013.09-2015.06,澳门大学,计算数学,硕士;
2015.09-2019.01,澳门大学,计算机科学,博士;
2019.02-2019.05,澳门大学,博士后访问学者;
论文：
1)Junwei Jin,Yanting Li, Tiejun Yang, Liang Zhao, Junwei Duan*,C. L. Philip Chen*,“Discriminative Group-Sparsity Constrained BroadLearning System for Visual Recognition”,Information Sciences,576: 800-818,2021(SCI, 中科院1区，JCR Q1).
2)Junwei Jin,Yanting Li, C. L. Philip Chen*,“PatternClassification withCorruptedLabeling viaRobustBroadLearningSystem”,IEEE Transactions onKnowledge and Data Engineering,pp:1-1,2021,DOI:10.1109/TKDE.2021.3049540(SCI, 中科院2区, CCF-A, JCR Q1).
3)Junwei Jin, Zhulin Liu, C. L. Philip Chen*,“Discriminative Graph Regularized Broad Learning System for Image Recognition”,Science China Information Sciences,61(11): 112209,2018 (SCI，中科院2区，JCR Q2).
4)Junwei Jin,C. L. Philip Chen*,“Regularized Robust Broad Learning System for Uncertain Data Modeling”,Neurocomputing,322: 58-69,2018 (SCI，中科院2区，JCR Q1).
5)Yanting Li,Junwei Jin*,Liang Zhao, Huaiguang Wu, Lijun Sun, C. L. Philip Chen,“A Neighborhood Prior Constrained Collaborative Representation for Classification”,International Journal of WaveletsMultiresolution and Information Processing,19(2): 2050073:1-2050073:22,2021(SCI, 中科院4区，JCR Q4).
6)Junwei Jin,Yanting Li*, Lijun Sun*, Jianyu Miao, C. L. Philip Chen,“A New Local Knowledge-Based Collaborative Representation for Image Recognition”,IEEE Access,8:81069–81079, 2020(SCI，中科院2区，JCR Q1).
7)Yanting Li, Junwei Jin*,“A Novel Two-Dimensional Unwinding Decomposition for Image Signals”,IEEE Access,7: 168700–168709,2019(SCI，中科院2区，JCR Q1).
8)Yanting Li,Junwei Jin*,C. L. Philip Chen, “A real-time classification model based on joint sparse-collaborative representation”,Journal of Real-Time Image Processing, DOI: 10.1007/s11554-021-01167-y, 2021 (SCI, 中科院3区，JCR Q3).
9)Junwei Duan*,Shuqi Mao, Junwei Jin,Zhiguo Zhou*, Long Chen,C. L. Philip Chen,“A novel GA-based optimized approach
for regional multimodal medical imagefusion with superpixel segmentation”,IEEE Access, 9:96353-96366,2021(SCI，中科院2区，JCR Q1).
10)Shuai Sui,Yongliang Zhan, Junwei Jin,C. L. Philip Chen*, Shaocheng Tong,“Adaptivefuzzydecentralizedcontrol forfractional-ordernonlinearlarge-scalesystemswithunmodeleddynamics”,IEEE Access, 9:142594-142604,2021(SCI，中科院2区，JCR Q1).
11)Yufeng Zhang,Zhe Feng, Junwei Jin,Wentao Gao, Hao Xu,Dengxiu Yu,“Time-varying formation control withsmooth switching communication”,AIP Advances,11, 105103 (2021); https://doi.org/10.1063/5.0065273(SCI，中科院4区，JCR Q2).
12)Chunhua Zhang,Junwei Jin, Haiwei Sun, Qin Sheng*, “A Spatially Sixth-order Hybrid L1-CCD Method for Solving Time Fractional SchrÖdinger Equations”,Applications of Mathematics, 66(2):213-232,2021(SCI, 中科院4区，JCR Q3).
13)Shuo Yang, Jingzhi Guo*,Junwei Jin,“An improved Id3 algorithm for medical data classification”,Computers & Electrical Engineering, 65:474-487, Jan 2018 (SCI).
14)Yanting Li,Junwei Jin*, Huaiguang Wu, Lijun Sun and C. L. Philip Chen, “Multi-resolution Collaborative Representation for Face Recognition”,IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2020 (EI).
15)Junwei Jin，C. L. Philip Chen*, Jin Zhou,“Image Recognition Using Manifold ConstrainedCollaborative Representation”,International Conference onSecurity, Pattern Analysis, and Cybernetics (SPAC), 2018 (EI).
16)Junwei Jin,C. L. Philip Chen*, Yanting Li,“Robust Broad Learning System for Uncertain Data Modeling”,International Conference on Systems, Man and Cybernetics(SMC), 2018 (EI).
17)Junwei Jin,C. L. Philip Chen*,“Convolutional Sparse Coding for Face Recognition”,International Conference on Informative and Cybernetics for Computational Social System(ICCSS), 2017 (EI).
18)Junwei Jin,C. L. Philip Chen*, Long Chen,“Metaface Block Sparse Bayesian Learning for Face Recognition”,32ndYouth Academic Annual Conference of Chinese Association of Automation (YAC), 2017 (EI).
项目：
1.金军委，判别型鲁棒宽度学习系统建模及优化研究，国家自然科学基金，2022.01-2024.12.
2.金军委，基于鲁棒宽度学习系统的无人仿生集群智能分群策略研究，河南省科技厅科技攻关项目，2022.01-2023.12
3.金军委，基于最大后验误差估计和流形学习的鲁棒宽度学习模型及应用研究，河南省教育厅自然科学项目，2021.01-2022.12
4. 金军委，基于宽度学习系统的储量霉变预测新方法研究，教育部粮食信息处理与控制重点实验室开放课题，2020.06-2022.06
5. 金军委，宽度学习系统及应用，河南工业大学高层次人才引进项目，2020.01-2022.12
