王前前
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王前前，现为西安电子科技大学通信工程学院菁英副教授，硕士生导师，2019年在西安电子科技大学通信与信息系统专业获得博士学位。2017.10—2018.10在美国东北大学访学。2019年6月在西安电子科技大学通信工程学院任教。主要研究方向是模式识别、机器学习、图像处理、数据挖掘、多模态聚类等。
获得2019博士后创新人才计划、中国博士后科学基金面上项目，陕西省自然基金面上/青年项目。获数据挖掘顶级会议IEEE ICDM 2018的 Student Travel Award，获中国图象图形学会2020石青云女科学家奖，陕西省2021优秀博士论文。获2022年校级优秀本科毕业设计（毕业论文）指导教师。获2020-2021学年校级“优秀本科生导学团队”荣誉称号。
在国际顶级期刊“IEEE Trans. Neural Networks and Learning Systems”，“IEEE Trans. Image Processing”和顶级国际会议（中科院A类会议）CVPR, AAAI, IJCAI等处发表和录用论文40余篇。担任中国图象图形学会女科技工作者委员会委员，SCI期刊Electronics的Special Issue Guest Editor， IJCAI 2019，AAAI 2023的Session Chair，担任IJCAI 2021的SPC member，国际一流期刊“IEEE Trans. Cybernetics”, “IEEE Trans. Image Processing”, “IEEE Trans. Neural Networks and Learning Systems”等期刊的审稿人。多次担任CCF A类会议AAAI，IJCAI，ACM MM的PC member。
个人主页：qianqian.world
团队介绍：https://web.xidian.edu.cn/qxgao/team.html
招生信息：
现有2024年入学研究生（保研、考研）名额，欢迎咨询：qqwang@xidian.edu.cn 或者 qianqian174@foxmail.com
欢迎通信工程、计算机、人工智能、数学、电子、网络与信息安全等相关专业保研和考研的同学联系。
发表论文：
2023年：
Han Lu, Quanxue Gao, Qianqian Wang, Ming Yang, Wei Xia，Centerless multi-view K-means based on the adjacency matrix，Proceedings of the AAAI Conference on Artificial Intelligence，37 (7), 8949-8956， (2023)（CCF A类会议）
Jing Li, Quanxue Gao, Qianqian Wang, Wei Xia, Xinbo Gao: Multi-View Clustering via Semi-non-negative Tensor Factorization. NeurIPS, 2023.（CCF A类会议）
Qian Zhou, Quanxue Gao, Qianqian Wang, Ming Yang, Xinbo Gao，Sparse discriminant PCA based on contrastive learning and class-specificity distribution，Neural Networks，167, 775-786 (2023)（中科院一区）
Zihao Zhang, Qianqian Wang, Zhiqiang Tao, Quanxue Gao, Wei Feng，Dropping Pathways Towards Deep Multi-View Graph Subspace Clustering Networks，Proceedings of the 31st ACM International Conference on Multimedia, 3259-3267 (2023)（CCF A类会议）
Wei Xia, Quanxue Gao, Qianqian Wang, Xinbo Gao, Chris Ding, Dacheng Tao: Tensorized Bipartite Graph Learning for Multi-View Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 5187- 5202 (2023)（中科院一区，ESI高被引2023）
Qianqian Wang, Zhiqiang Tao, Quanxue Gao, Licheng Jiao. Multi-view Subspace Clustering via Structured Multi-pathway Network, IEEE Trans. Neural Networks Learn. Syst., 2022. doi: 10.1109/TNNLS.2022.3213374.（中科院一区）
Qianqian Wang, Zhiqiang Tao, Wei Xia, Quanxue Gao, Xiaochun Cao, Licheng Jiao. Adversarial Multi-view Clustering Networks with Adaptive Fusion, IEEE Trans. Neural Networks Learn. Syst., 2022. doi:10.1109/TNNLS.2022.3145048.（中科院一区，ESI高被引2023）
2022年：
Wei Xia, Quanxue Gao, Qianqian Wang, Xinbo Gao: Tensor Completion-Based Incomplete Multiview Clustering. IEEE Trans. Cybern. 52(12): 13635-13644 (2022)（中科院一区）
Wei Xia, Qianqian Wang, Quanxue Gao, Xiangdong Zhang, Xinbo Gao: Self-Supervised Graph Convolutional Network for Multi-View Clustering. IEEE Trans. Multim. 24: 3182-3192 (2022)（中科院一区）
Qiang Wang, Gan Sun, Jiahua Dong, Qianqian Wang, Zhengming Ding: Continuous Multi-View Human Action Recognition. IEEE Trans. Circuits Syst. Video Technol. 32(6): 3603-3614 (2022)（中科院一区）
Gan Sun, Yang Cong, Qianqian Wang, Bineng Zhong, Yun Fu: Representative Task Self-Selection for Flexible Clustered Lifelong Learning. IEEE Trans. Neural Networks Learn. Syst. 33(4): 1467-1481 (2022)（中科院一区，ESI高被引2023）
Guoshuai Sheng, Qianqian Wang, Chengquan Pei, Quanxue Gao: Contrastive deep embedded clustering. Neurocomputing 514: 13-20 (2022)（中科院二区）
Qin Li, Huihui He, Hong Lai, Tie Cai, Qianqian Wang, Quanxue Gao: Enhanced nuclear norm based matrix regression for occluded face recognition. Pattern Recognit. 126: 108585 (2022)（中科院一区）
2021年：
Qianqian Wang, Huanhuan Lian, Gan Sun, Quanxue Gao, Licheng Jiao: iCmSC: Incomplete Cross-Modal Subspace Clustering. IEEE Trans. Image Process. 30: 305-317 (2021)（中科院一区）
Qianqian Wang, Zhengming Ding, Zhiqiang Tao, Quanxue Gao, Yun Fu: Generative Partial Multi-View Clustering With Adaptive Fusion and Cycle Consistency. IEEE Trans. Image Process. 30: 1771-1783 (2021)（中科院一区）
Qianqian Wang, Quanxue Gao, Linlu Wu, Gan Sun, Licheng Jiao: Adversarial Multi-Path Residual Network for Image Super-Resolution. IEEE Trans. Image Process. 30: 6648-6658 (2021)（中科院一区）
Qianqian Wang, Jiafeng Cheng, Quanxue Gao, Guoshuai Zhao, Licheng Jiao: Deep Multi-View Subspace Clustering With Unified and Discriminative Learning. IEEE Trans. Multim. 23: 3483-3493 (2021)（中科院一区）
Qianqian Wang, Wei Xia, Zhiqiang Tao, Quanxue Gao, Xiaochun Cao: Deep Self-Supervised t-SNE for Multi-modal Subspace Clustering. ACM Multimedia. 2021: 1748-1755（CCF A类会议）
Wei Xia, Quanxue Gao, Qianqian Wang, Xinbo Gao: Regression-based clustering network via combining prior information. Neurocomputing 448: 324-332 (2021)（中科院二区）
2020年：
Quanxue Gao, Huanhuan Lian, Qianqian Wang, Gan Sun: Cross-Modal Subspace Clustering via Deep Canonical Correlation Analysis. AAAI 2020: 3938-3945（CCF A类会议）
Jiafeng Cheng, Qianqian Wang, Zhiqiang Tao, De-Yan Xie, Quanxue Gao: Multi-View Attribute Graph Convolution Networks for Clustering. IJCAI 2020: 2973-2979（CCF A类会议）
Qianqian Wang, Quanxue Gao, Gan Sun, Chris Ding:Double robust principal component analysis. Neurocomputing 391: 119-128 (2020)（中科院二区）
Gan Sun, Yang Cong, Qianqian Wang, Jun Li, Yun Fu: Lifelong Spectral Clustering. AAAI 2020: 5867-5874（CCF A类会议）
Tao Zhang, Yang Cong, Gan Sun, Qianqian Wang, Zhengming Ding: Visual Tactile Fusion Object Clustering. AAAI 2020: 10426-10433（CCF A类会议）
DeYan Xie, Wei Xia, Qianqian Wang, Quanxue Gao, Song Xiao: Multi-view clustering by joint manifold learning and tensor nuclear norm. Neurocomputing 380: 105-114 (2020)（中科院二区）
DeYan Xie, Quanxue Gao, Qianqian Wang, Xiangdong Zhang, Xinbo Gao: Adaptive latent similarity learning for multi-view clustering. Neural Networks 121: 409-418 (2020)（中科院一区）
Quanxue Gao, Zhizhen Wan, Ying Liang, Qianqian Wang, Yang Liu, Ling Shao: Multi-view projected clustering with graph learning. Neural Networks 126: 335-346 (2020)（中科院一区）
2019年：
Zhaoyang Li, Qianqian Wang, Zhiqiang Tao, Quanxue Gao, Zhaohua Yang:Deep Adversarial Multi-view Clustering Network. IJCAI 2019: 2952-2958（CCF A类会议）
Quanxue Gao, Jiafeng Cheng, DeYan Xie, Pu Zhang, Wei Xia, Qianqian Wang: Tensor Linear Regression and Its Application to Color Face Recognition. ICCV Workshops 2019: 523-531（CCF A类会议）
2018年及以前：
Qianqian Wang, Quanxue Gao, Xinbo Gao, Feiping Nie: ℓ2, p -Norm Based PCA for Image Recognition. IEEE Trans. Image Process. 27(3): 1336-1346 (2018)（中科院一区）
Qianqian Wang, Quanxue Gao, De-Yan Xie, Xinbo Gao, Yong Wang: Robust DLPP With Nongreedy ℓ1-Norm Minimization and Maximization. IEEE Trans. Neural Networks Learn. Syst. 29(3): 738-743 (2018)（中科院一区）
Qianqian Wang, Zhengming Ding, Zhiqiang Tao, Quanxue Gao, Yun Fu: Partial Multi-view Clustering via Consistent GAN. ICDM 2018: 1290-1295（CCF B类会议）
Yang Liu, Shuangshuang Zhao, Qianqian Wang, Quanxue Gao: Learning more distinctive representation by enhanced PCA network. Neurocomputing 275: 924-931 (2018)（中科院二区）
Mengyuan Li, Jing Wang, Qianqian Wang, Quanxue Gao: Trace ratio 2DLDA with L1-norm optimization. Neurocomputing 266: 216-225 (2017)（中科院二区）
Qianqian Wang, Lan Ma, Quanxue Gao, Yunsong Li, Yunfang Huang, Yang Liu: Adaptive maximum margin analysis for image recognition. Pattern Recognit. 61: 339-347 (2017)（中科院一区）
Qianqian Wang, Quanxue Gao, Xinbo Gao, Feiping Nie: Optimal mean two-dimensional principal component analysis with F-norm minimization. Pattern Recognit. 68: 286-294 (2017)（中科院一区）
Qianqian Wang, Quanxue Gao: Two-Dimensional PCA with F-Norm Minimization. AAAI 2017: 2718-2724（CCF A类会议）
Qianqian Wang, Quanxue Gao, Xinbo Gao, Feiping Nie: Angle Principal Component Analysis. IJCAI 2017: 2936-2942（CCF A类会议）
Qianqian Wang, Fang Chen, Quanxue Gao, Xinbo Gao, Feiping Nie: On the schatten norm for matrix based subspace learning and classification. Neurocomputing 216: 192-199 (2016)（中科院二区）
Qianqian Wang, Quanxue Gao: Robust 2DPCA and Its Application. CVPR Workshops 2016: 1152-1158（CCF A类会议）
Quanxue Gao, Qianqian Wang, Yunfang Huang, Xinbo Gao, Xin Hong, Hailin Zhang: Dimensionality Reduction by Integrating Sparse Representation and Fisher Criterion and its Applications. IEEE Trans. Image Process. 24(12): 5684-5695 (2015)（中科院一区）
Qianqian Wang, Xiaolei Hu, Quanxue Gao, Bing Li, Yong Wang: Global-local fisher discriminant approach for face recognition. Neural Comput. Appl. 25(5): 1137-1144 (2014)（中科院二区）
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多模态学习
数据挖掘
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