个人简介

张睿，男，汉族，1986年3月生，博士，副教授。在西北工业大学计算机学院获得计算机科学与技术专业工学博士学位，并于2019-2020年间由国家留学基金委公派至美国亚利桑那州立大学交流访问。主持国家自然科学基金面上项目，博士后科学基金面上资助项目，博士后科学基金特别资助项目等。担任IJCAI 2019程序委员会高级委员，NeurIPS 2020与IJCAI 2020程序委员会委员。担任IEEE TPAMI、IEEE TNNLS、IEEE TCYB、IEEE TKDE、IEEE TIP、IEEE TFS、IEEE TSP以及Pattern Recognition等期刊的长期审稿人。

承担课程:

本科生课程：科学大数据管理、大数据安全与保密。

研究方向

大数据管理与挖掘、保密科学中的大数据安全。

学术成果

期刊论文

[1] R. Zhang, Y. Zhang, C. Lu, and X. Li, "Unsupervised Graph Embedding via Adaptive Graph Learning," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 4, pp. 5329-5336, 2023.

[2] R. Zhang, Z. Jiao, H. Zhang, and X. Li, "Manifold Neural Network With Non-Gradient Optimization," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 3, pp. 3986-3993, 2023.

[3] R. Zhang, H. Zhang, and X. Li, "Robust Multi-Task Learning with Flexible Manifold Constraint," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 43, no. 6, pp. 2150-2157, 2021.

[4] X. Li, H. Zhang, and R. Zhang*, "Matrix Completion via Non-Convex Relaxation and Adaptive Correlation Learning," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 2, pp. 1981-1991, 2023.

[5] X. Li, H. Zhang, and R. Zhang*, "Adaptive Graph Auto-Encoder for General Data Clustering," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 44, no. 12, pp. 9725-9732, 2022.

[6] H. Zhang, J. Shi, R. Zhang, and X. Li, "Non-Graph Data Clustering via O(n) Bipartite Graph Convolution," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), doi: 10.1109/TPAMI.2022.3231470.

[7] R. Zhang, W. Zhang, P. Li, and X. Li, "Graph Convolution RPCA With Adaptive Graph," IEEE Transactions on Image Processing (TIP), vol. 31, pp. 6062-6071, 2022.

[8] R. Zhang and X. Li, "Unsupervised Feature Selection Via Data Reconstruction and Side Information," IEEE Transactions on Image Processing (TIP), vol. 29, pp. 8097-8106, 2020.

[9] R. Zhang, F. Nie, M. Guo, X. Wei, and X. Li, "Joint Learning of Fuzzy K-Means and Nonnegative Spectral Clustering with Side Information," IEEE Transactions on Image Processing (TIP), vol. 28, no. 5, pp. 2152-2162, 2019.

[10] X. Li, H. Zhang, R. Zhang*, and F. Nie, "Discriminative and Uncorrelated Feature Selection with Constrained Spectral Analysis in Unsupervised Learning," IEEE Transactions on Image Processing (TIP), vol. 29, no. 1, pp. 2139-2149, 2020.

[11] F. Nie, S. Yang, R. Zhang*, and X. Li, "A General Framework for Auto-weighted Feature Selection via Global Redundancy Minimization," IEEE Transactions on Image Processing (TIP), vol. 28, no. 5, pp. 2428-2438, 2019.

[12] F. Nie, H. Zhang, R. Zhang, and X. Li, "Robust Multiple Rank-k Bilinear Projections for Unsupervised Learning," IEEE Transactions on Image Processing (TIP), vol. 28, no. 5, pp. 2574-2583, 2019.

[13] R. Zhang and X. Li, "Regularized Regression With Fuzzy Membership Embedding for Unsupervised Feature Selection," IEEE Transactions on Fuzzy Systems (TFS), vol. 29, no. 12, pp. 3743-3753, 2021.

[14] R. Zhang, X. Li, H. Zhang, and F. Nie, "Deep Fuzzy K-Means with Adaptive Loss and Entropy Regularization," IEEE Transactions on Fuzzy Systems (TFS), vol. 28, no. 11, pp. 2814-2824, 2020.

[15] T. Wu, R. Zhang*, Z. Jiao, X. Wei, and X. Li, "Adaptive Spectral Rotation via Joint Cluster and Pairwise Structure," IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 35, no. 1, pp. 71-81, 2023.

[16] X. Li, P. Li, H. Zhang, K. Zhu, and R. Zhang*, "Pivotal-Aware Principal Component Analysis," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023, doi: 10.1109/TNNLS.2023.3252602.

[17] X. Li, Y. Zhang, and R. Zhang*, "Self-Weighted Unsupervised LDA," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 34, no. 3, pp. 1627-1632, 2023.

[18] X. Li, Y. Zhang, and R. Zhang*, "Semisupervised Feature Selection via Generalized Uncorrelated Constraint and Manifold Embedding," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 33, no. 9, pp. 5070-5079, 2022.

[19] R. Zhang, H. Zhang, and X. Li, "Maximum Joint Probability With Multiple Representations for Clustering," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 33, no. 9, pp. 4300-4310, 2022.

[20] R. Zhang, H. Zhang, X. Li, and S. Yang, "Unsupervised Feature Selection With Extended OLSDA via Embedding Nonnegative Manifold Structure," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 33, no. 5, pp. 2274-2280, 2022.

[21] R. Zhang, Y. Zhang, and X. Li, "Unsupervised Feature Selection via Adaptive Graph Learning and Constraint," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 33, no. 3, pp. 1355-1362, 2022.

[22] R. Zhang, X. Li, T. Wu, and Y. Zhao, "Data Clustering via Uncorrelated Ridge Regression," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 32, no. 1, pp. 450-456, 2021.

[23] X. Li, R. Zhang*, Q. Wang, and H. Zhang, "Autoencoder Constrained Clustering With Adaptive Neighbors," IEEE Transactions on Neural Networks and Learning Systems  (TNNLS), vol. 32, no. 1, pp. 443-449, 2021.

[24] R. Zhang, H. Zhang, X. Li, and F. Nie, "Adaptive Robust Low-rank 2D Reconstruction with Steerable Sparsity," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 31, no. 9, pp. 3754-3759, 2020.

[25] R. Zhang, F. Nie, Y. Wang, and X. Li, "Unsupervised Feature Selection via Adaptive Multi-Measure Fusion," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 9, pp. 2886-2892, 2019. （X. Li, H. Zhang, R. Zhang*, and F. Nie, "Generalized Uncorrelated Regression Model with Adaptive Graph for Unsupervised Feature Selection," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 5, pp. 1587-1595, 2019.

[26] R. Zhang, F. Nie, and X. Li, "Semi-Supervised Learning with Parameter-Free Similarity of Label and Side Information," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 2, pp. 405-414, 2019.

[27] R. Zhang, F. Nie, and X. Li, "Self-Weighted Supervised Discriminative Feature Selection," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 29, no. 8, pp. 3913-3918, 2018.

[28] R. Zhang, F. Nie, and X. Li, "Regularized Class-Specific Subspace Classifier," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 28, no. 11, pp. 2738-2747, 2017.

[29] Y. Liu, R. Zhang, F. Nie, and X. Li, "Supervised Dimensionality Reduction Methods with Recursive Regression," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 31, no. 9, pp. 3269-3279, 2020.

[30] R. Zhang, F. Nie, X. Li, and X. Wei, "Feature Selection with Multi-view Data: A Survey," Information Fusion, vol. 50, pp. 158-167, 2019.

[31] P. Li, W. Zhang, C. Lu, R. Zhang*, and Xuelong Li, "Robust Kernel Principal Component Analysis with Optimal Mean, " Neural Networks, vol. 152, pp. 347-352, 2022.

[32] F. Nie, R. Zhang*, and X. Li, "A generalized power iteration method for solving quadratic problem on the Stiefel manifold," Science China Information Sciences, vol. 60, no. 11, pp. 112101, 2017.

[33] H. Zhang, F. Nie, R. Zhang, and X. Li, "Auto-weighted 2-Dimensional Maximum Margin Criterion," Pattern Recognition, vol. 83, pp. 220-229, 2018.

[34] R. Zhang, F. Nie, and X. Li, "Self-Weighted Spectral Clustering with Parameter-Free Constraint," Neurocomputing, vol. 241, pp. 164-170, 2017.

[35] R. Zhang, F. Nie, and X. Li, "Feature Selection under Regularized Orthogonal Least Square Regression with Optimal Scaling," Neurocomputing, vol. 273, pp. 547-553, 2018.

[36] T. Wu, Y. Zhou, R. Zhang, Y. Xiao, and F. Nie, "Self-Weighted Discriminative Feature Selection via Adaptive Redundancy Minimization," Neurocomputing, vol. 275, pp. 2824-2830, 2018.

[37] H. Zhang, R. Zhang, F. Nie, and X. Li, "An Efficient Framework for Unsupervised Feature Selection," Neurocomputing, vol. 366, pp. 194-207, 2019.

[38] H. Zhang, R. Zhang, X. Li, and Y. Xu, "Robust Multi-View Fuzzy Clustering via Softmin," Neurocomputing, vol. 458, pp. 47-55, 2021. Y. Zhao, M. Qiao, H. Wang, R. Zhang, D. Wang and K. Xu, "Friendship Inference in Mobile Social Networks: Exploiting Multi-Source Information With Two-Stage Deep Learning Framework," IEEE/ACM Transactions on Networking, 2022, doi: 10.1109/TNET.2022.3198105.

[39] Y. Zhao, H. Wang, H. Su, L. Zhang, R. Zhang, D. Wang, and K. Xu, "Understand Love of Variety in Wireless Data Market under Sponsored Data Plans," IEEE Journal on Selected Areas in Communications, vol. 38, no. 4, pp. 766-781, 2020.

[40] 邱云飞, 潘博, 张睿, 王万里，魏宪. 嵌入式深度神经网络高光谱图像聚类[J].中国图象图形学报, 2020(1):13.

[41] 肖成龙，张重鹏，王珊珊，张睿，王万里，魏宪. 基于流形正则化与成对约束的深度半监督谱聚类算法[J]. 系统科学与数学, 2020, 40(8): 1325-1341.

会议论文

[1] R. Zhang and H. Tong, "Robust Principal Component Analysis with Adaptive Neighbors," Thirty-third Conference on Neural Information Processing Systems (NeurIPS), pp. 6959-6967, 2019.

[2] Y. Zhao, M. Qiao, H. Wang, R. Zhang, D. Wang, K. Xu, and Q. Tan, "TDFI: Two-stage Deep Learning Framework for Friendship Inference via Multi-source Information," IEEE International Conference on Computer Communications (INFOCOM), pp. 1981-1989, 2019.

[3] R. Zhang, H. Tong, Y. Xia, and Y. Zhu, "Robust Embedded Deep K-means Clustering," ACM International Conference on Information and Knowledge Management (CIKM), pp. 1181-1190, 2019.

[4] R. Zhang, H. Tong, and Y. Hu, "Adaptive Feature Redundancy Minimization," ACM International Conference on Information and Knowledge Management (CIKM), pp. 2417-2420, 2019.

[5] S. Yang, R. Zhang*, F. Nie, and X. Li, "Unsupervised Feature Selection Based on Reconstruction Error Minimization," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2108-2111, 2019.

[6] H. Zhang, R. Zhang*, F. Nie, and X. Li, "A Generalized Uncorrelated Ridge Regression with Nonnegative Labels for Unsupervised Feature Selection," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2781-2785, 2018.

[7] M. Guo, R. Zhang, F. Nie, and X. Li, "Embedding Fuzzy K-Means with Nonnegative Spectral Clustering via Incorporating Side Information," ACM International Conference on Information and Knowledge Management (CIKM), pp. 1567-1570, 2018.

[8] R. Zhang, F. Nie, and X. Li, "Semi-Supervised Classification via both Label and Side Information," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2417-2421, 2017.

[9] R. Zhang, F. Nie, and X. Li, "Embedded Clustering via Robust Orthogonal Least Square Discriminant Analysis," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2332-2336, 2017.

[10]R. Zhang, F. Nie, and X. Li, "Auto-Weighted Two-Dimensional Principal Component Analysis with Robust Outliers," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6065-6069, 2017.

[11]G. Cai, R. Zhang*, F. Nie, and X. Li, "Feature Selection via Incorporating Stiefel Manifold in Relaxed K-Means," IEEE International Conference on Image Processing (ICIP), pp. 1503-1507, 2018.

[12]R. Zhang, F. Nie, and X. Li, "Projected clustering via robust orthogonal least square regression with optimal scaling," International Joint Conference on Neural Networks (IJCNN), pp. 2784-2791, 2017.

承担项目

2023.01 – 2026.12 国家自然科学基金委员会，面上项目，面向数据间图拓扑关系的表征学习研究，62276213，53万元，在研，主持

2023.01 – 2025.12 科技部，科技创新2030 –“新一代人工智能”重大项目，面向通用视觉的机器学习理论与方法，2022ZD0160302，120万元，在研，子课题负责人

2021.12 – 2022.12 中国飞机强度研究所，横向项目，基于机器学习的飞机结构状态评估技术研究，45万元，结题，主持

2019.06 – 2020.06 中国博士后科学基金会，特别资助，L1范数损失支持向量机的低维数据快速分类，2019T120960，18万元，结题，主持

2018.12 – 2019.12 西安市人力资源和社会保障局，西安市博士后创新基地项目资助（特等），非线性数据的降维问题，15万元，结题，主持

2018.11 – 2019.11 中国博士后科学基金会，面上资助（二等），高维数据下的数据重构与线性降维问题，2018M643765，5万元，结题，主持

2018.01 – 2020.12 国家自然科学基金委员会, 应急管理项目, 开放环境中不确定条件下的新型智能感知与行为理解方法研究, 61751202, 220万元, 结题, 主要参与人