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 Broad Learning 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*, “Pattern Classification with Corrupted Labeling via Robust Broad Learning System”, IEEE Transactions on Knowledge 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 Wavelets Multiresolution 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, “Adaptive fuzzy decentralized control for fractional-order nonlinear large-scale systems with unmodeled dynamics”, 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 with smooth 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 Constrained Collaborative Representation”, International Conference on Security, 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”, 32nd Youth 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，welcome皇冠地址高层次人才引进项目，2020.01-2022.12
