個人簡介

張睿，男，漢族，1986年3月生，博士，副教授，現(xiàn)任大數(shù)據(jù)安全與保密系支部書記、副主任。在西北工業(yè)大學計算機學院獲得計算機科學與技術專業(yè)工學博士學位，并于2019-2020年間由國家留學基金委公派至美國亞利桑那州立大學交流訪問。主持國家自然科學基金面上項目，博士后科學基金面上資助項目，博士后科學基金特別資助項目等。擔任IJCAI 2019程序委員會高級委員，NeurIPS 2020與IJCAI 2020程序委員會委員。擔任IEEE TPAMI、IEEE TNNLS、IEEE TCYB、IEEE TKDE、IEEE TIP、IEEE TFS、IEEE TSP以及Pattern Recognition等期刊的長期審稿人。

承擔課程:

本科生課程：科學大數(shù)據(jù)管理、大數(shù)據(jù)安全與保密。

研究方向

大數(shù)據(jù)管理與挖掘、保密科學中的大數(shù)據(jù)安全。

學術成果

期刊論文

[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] 邱云飛, 潘博, 張睿, 王萬里，魏憲. 嵌入式深度神經(jīng)網(wǎng)絡高光譜圖像聚類[J].中國圖象圖形學報, 2020(1):13.

[41] 肖成龍，張重鵬，王珊珊，張睿，王萬里，魏憲. 基于流形正則化與成對約束的深度半監(jiān)督譜聚類算法[J]. 系統(tǒng)科學與數(shù)學, 2020, 40(8): 1325-1341.

會議論文

[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.

承擔項目

2023.01 – 2026.12 國家自然科學基金委員會，面上項目，面向數(shù)據(jù)間圖拓撲關系的表征學習研究，62276213，53萬元，在研，主持

2023.01 – 2025.12 科技部，科技創(chuàng)新2030 –“新一代人工智能”重大項目，面向通用視覺的機器學習理論與方法，2022ZD0160302，120萬元，在研，子課題負責人

2021.12 – 2022.12 中國飛機強度研究所，橫向項目，基于機器學習的飛機結構狀態(tài)評估技術研究，45萬元，結題，主持

2019.06 – 2020.06 中國博士后科學基金會，特別資助，L1范數(shù)損失支持向量機的低維數(shù)據(jù)快速分類，2019T120960，18萬元，結題，主持

2018.12 – 2019.12 西安市人力資源和社會保障局，西安市博士后創(chuàng)新基地項目資助（特等），非線性數(shù)據(jù)的降維問題，15萬元，結題，主持

2018.11 – 2019.11 中國博士后科學基金會，面上資助（二等），高維數(shù)據(jù)下的數(shù)據(jù)重構與線性降維問題，2018M643765，5萬元，結題，主持

2018.01 – 2020.12 國家自然科學基金委員會, 應急管理項目, 開放環(huán)境中不確定條件下的新型智能感知與行為理解方法研究, 61751202, 220萬元, 結題, 主要參與人