Education

• Ph.D., Tsinghua University, Beijing, China- August, 2003 - June, 2009

Biography

Feiping Nie, a research assistant professor in the University of Texas at Arlington. My research interesting are machine learning and its application such as pattern recognition, data mining and computer vision. I am an expert on these areas, and have published more than 100 papers in the prestigious journals and conferences such as TPAMI, TNNLS, TIP, ICML, NIPS, KDD, IJCAI, AAAI, CVPR, ICCV, etc.

Research Interest

Machine Learning and Data Mining

• Graph Based Learning
• Active Learning
• Gaussian Process and Kernel Machines
• Boosting and Ensembles

Pattern Recognition and Image Processing

Computer Vision
Bioinformation

Professional Activities:

• Research Professor, University of Texas, Arlington, USA-March, 2015 - Present
• Research Associate Professor, University of Texas, Arlington, USA- October, 2014 - March, 2015
• Research Assistant Professor, University of Texas, Arlington, USA -December, 2010 - October, 2014
• PostDoctoral Research Associate, University of Texas, Arlington, USA -November, 2009 - December, 2010
• Research Associate, Nanyang Technological University, Singapore-September, 2008 - November, 2009

Honor and awards:

Awards ECML PKDD. Best Student Paper Runner-up Award. 2011.First Class Award for Excellent Doctoral Thesis of Tsinghua University (Top 2%), 2009. PAKDD. Best Paper Award Honorable Mention. 2007.

Publications

1. Hong Tao, Chenping Hou, Feiping Nie∗, Dongyun Yi. Effective Discriminative Feature Selection with Non-trivial Solution. IEEE Transactions on Neural Networks and Learning Systems (TNNLS),  to  appear.
2. Xiaojun Chang, Haoquan Shen, Feiping Nie∗, Sen Wang, Yi Yang and Xiaofang Zhou. Compound Rank-k Projections for Bilinear Analysis.  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), to appear.
3. De Wang, Feiping Nie, Heng Huang. Global Redundancy Minimization for Feature Ranking.
4. IEEE Transactions on Knowledge and Data Engineering (TKDE), to appear, 2015.
5. Hua Wang, Feiping Nie, Heng Huang. Large-Scale Cross-Language Web Page Classification via Dual Knowledge Transfer Using Fast Nonnegative Matrix Tri-Factorization. ACM Transactions on Knowledge Discovery from Data (TKDD), to appear.
6. Yi Yang, Zhigang Ma, Feiping Nie∗, Xiaojun Chang, Alexander G. Hauptmann. MultiClass Active Learning by Uncertainty Sampling with Diversity Maximization. International Journal of Computer Vision (IJCV), to appear.
7. Rong Wang, Feiping Nie, Xiaojun Yang, Feifei Gao and Minli Yao. Robust 2DPCA with Non- Greedy £1-Norm Maximization for Image Analysis. IEEE Transactions on Cybernetics (TC), to appear.
8. Chenping Hou, Feiping Nie, Dongyun Yi, Dacheng Tao. Discriminative Embedded Clustering: A Framework for Grouping High Dimensional Data. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), to appear.
9. Yang Yang, Zhigang Ma, Yi Yang, Feiping Nie and Heng Tao Shen. Multi-Task Spectral Clustering by Exploring Inter-task Correlation. IEEE Transactions on Cybernetics (TC), to appear.
10. Feiping Nie, Hua Wang, Heng Huang, Chris Ding. Joint Schatten p-Norm and £p-Norm Robust Matrix Completion for Missing Value Recovery. Knowledge and Information Systems (KAIS), to appear.
11. Zhigang Ma, Yi Yang, Feiping Nie, Nicu Sebe, Shuicheng Yan, Alexander G. Hauptmann.
12. Harnessing Lab Knowledge for Real-World Action Recognition. International Journal of Computer Vision (IJCV), 109(1-2):60–73, 2014.
13. Guorong Wu, Qian Wang, Daoqiang Zhang, Feiping Nie, Heng Huang, Dinggang Shen. A Generative Probability Model of Joint Label Fusion for Multi-Atlas Based Brain Segmentation. Medical Image Analysis (MIA), 18(6):881–890, 2014.
14. Chenping Hou, Feiping Nie, Changshui Zhang, Dongyun Yi, Yi Wu. Multiple Rank MultiLinear SVM for Matrix Data Classification. Pattern Recognition (PR), 47(1):454–469, 2014.
15. Chenping Hou, Feiping Nie, Xuelong Li, Dongyun Yi, Yi Wu. Joint Embedding Learning and Sparse Regression: A Framework for Unsupervised Feature Selection. IEEE Transactions on Cybernetics (TC), 44(6):793-804, 2014.
16. Chenping Hou, Feiping Nie, Hua Wang, Dongyun Yi, Changshui Zhang. Learning high- dimensional correspondence via manifold learning and local approximation. Neural Computing
17. & Applications (NCA), 24(7-8):1555–1568, 2014.
18. Jin Huang, Feiping Nie, Heng Huang, Chris Ding. Robust Manifold Non-Negative Matrix Fac- torization. ACM Transactions on Knowledge Discovery from Data (TKDD), 8(3):11, 2013.
19. Jin Huang, Feiping Nie, Heng Huang, Yicheng Tu, Yu Lei. Social Trust Prediction Using Heterogeneous Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), 7(4):17, 2013.
20. Hua Wang, Feiping Nie, Heng Huang, Chris Ding.  Predicting Protein-Protein Interactions from Multimodal Biological Data Sources via Nonnegative Matrix Factorization. Journal of Computational Biology (JCB), 20(4):344–358, 2013. (invited paper)
21. Chenping Hou, Feiping Nie, Changshui Zhang, Yi Wu. Learning a Subspace for Clustering via Pattern Shrinking. Information Processing & Management (IPM), 49(4):871–883, 2013.
22. Yun Liu, Feiping Nie∗, Jigang Wu, Lihui Chen.  Efficient Semi-supervised Feature Selection with Noise Insensitive Trace Ratio Criterion. Neurocomputing, 105:12–18, 2013.
23. Chenping Hou, Feiping Nie, Dongyun Yi, Yi Wu. Efficient Image Classification via Multiple Rank Regression. IEEE Transactions on Image Processing (TIP), 22(1):340–352, 2013.
24. Shiming Xiang, Feiping Nie, Gaofeng Meng, Chunhong Pan, Changshui Zhang. Discriminative Least Squares Regression for Multiclass Classification and Feature Selection. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 23(11):1738–1754, 2012.
25. Hua Wang, Feiping Nie, Heng Huang, Jingwen Yan, Sungeun Kim, Kwangsik Nho, Shannon Risacher, Andrew Saykin and Li Shen, ADNI. From Phenotype to Genotype: An Association Study of Candidate Longitudinal Phenotypic Markers to Alzheimer’s Disease Relevant SNPs. Bioinformatics, 28(18): i619–i625, 2012. (ECCB 2012 issue, 48/341=14.1%).
26. Zhigang Ma, Feiping Nie, Yi Yang, Jasper Uijlings, Nicu Sebe, Alexander G. Hauptmann.
27. Discriminating Joint Feature Analysis for Multimedia Content Understanding.  IEEE Trans- actions on Multimedia (TMM), 14(6):1662–1672, 2012.
28. Shizhun Yang, Chenping Hou, Feiping Nie, Yi Wu. Unsupervised maximum margin feature selection via L2,1-norm minimization. Neural Computing & Applications (NCA), 21(7):1791– 1799, 2012.
29. Zhigang Ma, Feiping Nie, Yi Yang, Jasper Uijlings, Nicu Sebe. Web Image Annotation via  Subspace-Sparsity Collaborated Feature Selection.   IEEE Transactions on Multimedia (TMM), 14(4):1021–1030, 2012.
30. Hua Wang, Feiping Nie, Heng Huang, Shannon Leigh Risacher, Andrew Saykin and Li Shen, ADNI. Identifying Disease Sensitive and Quantitative Trait Relevant Biomarkers from Heterogeneous Imaging Genetics Data via Sparse Multi-Modal Multi-Task Learning. Bioinformat- ics, 28(12):i127–i136, 2012. (ISMB 2012 issue, 36/268=13.4%).
31. Feiping Nie, Shiming Xiang, Yun Liu, Chenping Hou, Changshui Zhang. Orthogonal vs. Un- correlated Least Squares Discriminant Analysis for Feature Extraction. Pattern Recognition Letters (PRL), 33(5): 485–491, 2012.
32. Hua Wang∗, Feiping Nie∗, Heng Huang, Sungeun Kim, Kwangsik Nho, Shannon Risacher, An- drew J Saykin, Li Shen, ADNI. Identifying Quantitative Trait Loci via Group-Sparse Multi- Task Regression and Feature Selection: An Imaging Genetics Study of the ADNI Cohort. Bioinformatics, 28(2): 229–237, 2012.
33. Yi Huang, Dong Xu, Feiping Nie. Semi-supervised Dimension Reduction using Trace Ratio Cri- terion. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 23(3):519– 526, 2012. Yi Yang, Fei Wu, Feiping Nie, Heng Tao Shen, Yueting Zhuang, Alexander G. Hauptmann.
34. Web & Personal Image Annotation by Mining Label Correlation with Relaxed Visual Graph Embedding. IEEE Transactions on Image Processing (TIP), 21(3): 1339–1351, 2012.
35. Yi Yang, Feiping Nie, Dong Xu, Jiebo Luo, Yueting Zhuang, Yunhe Pan. A Multimedia  Retrieval Framework based on Semi-Supervised Ranking and Relevance Feedback. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 34(4):723–742, 2012.
36. Yi Huang, Dong Xu, Feiping Nie. Patch Distribution Compatible Semi-Supervised Dimension Reduction for Face and Human Gait Recognition. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 22(3):479–488, 2012.
37. Feiping Nie, Dong Xu, Xuelong Li. Initialization Independent Clustering with Actively Self- Training Method. IEEE Transactions on Systems, Man and Cybernetics, Part B (TSMCB), 42(1):17–27,  2012.
38. Feiping Nie, Zinan Zeng, Ivor Tsang, Dong Xu, Changshui Zhang. Spectral Embedded Clustering:  A Framework for In-Sample and Out-of-Sample Spectral Clustering. IEEE Transactions on Neural Networks (TNN), 22(11):1796–1808, 2011.
39. Shiming Xiang, Feiping Nie, Chunhong Pan, Changshui Zhang. Regression Reformulations of LLE and LTSA with Locally Linear Transformation. IEEE Transactions on Systems, Man and Cybernetics, Part B (TSMCB), 41(5):1250–1262, 2011.
40. Cheng Chen, Yueting Zhuang, Feiping Nie, Yi Yang, Fei Wu, Jun Xiao. Learning a 3D Human Pose Distance Metric from Geometric Pose Descriptor. IEEE Transactions on Visualization and Computer Graphics (TVCG), 17(11):1676–1689, 2011.
41. Chenping Hou, Feiping Nie, Fei Wang, Changshui Zhang, Yi Wu. Semi-Supervised Learning Using Negative Labels. IEEE Transactions on Neural Networks (TNN), 22(3):420–432, 2011.
42. Feiping Nie, Dong Xu, Xuelong Li, Shiming Xiang. Semi-Supervised Dimensionality Reduction and Classification through Virtual Label Regression. IEEE Transactions on Systems, Man and Cybernetics, Part B (TSMCB), 41(3):675-685, 2011.
43. Shiming Xiang, Chunhong Pan, Feiping Nie, Changshui Zhang. Interactive Image Segmentation with Multiple Linear Reconstructions in Windows. IEEE Transactions on Multimedia (TMM), 13(2):342–352, 2011.
44. Cheng Chen, Yi Yang, Feiping Nie, Jean-Marc Odobez. 3D Human Pose Recovery from Monocular Images via Efficient Visual Feature Selection. Computer Vision and Image Understanding (CVIU), 115(3):290–299, 2011.
45. Dijun Luo, Heng Huang, Chris Ding, Feiping Nie. On The Eigenvectors of p-Laplacian. Machine Learning (ML), 81(1):37–51, 2010.
46. Shiming Xiang, Chunhong Pan, Feiping Nie, Changshui Zhang. TurboPixel Segmentation Using Eigen-Images. IEEE Transactions on Image Processing (TIP), 19(11):3024–3034, 2010.
47. Yi Yang, Dong Xu, Feiping Nie, Shuicheng Yan, Yueting Zhuang. Image Clustering using Local Discriminant Models and Global Integration. IEEE Transactions on Image Processing (TIP), 19(10):2761–2773, 2010.
48. Feiping Nie, Dong Xu, Ivor W. Tsang, Changshui Zhang. Flexible Manifold Embedding: A Framework for Semi-supervised and Unsupervised Dimension Reduction. IEEE Transactions on Image Processing (TIP), 19(7):1921–1932, 2010.
49. Fei Wu, Wenhua Wang, Yi Yang, Yueting Zhuang, Feiping Nie. Classification by Semi- supervised Discriminative Regularization. Neurocomputing, 73(10-12):1641–1651, 2010.
50. Shiming Xiang, Feiping Nie, Chunxia Zhang, Changshui Zhang. Semi-Supervised Classification via Local Spline Regression. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 32(11):2039–2053, 2010.
51. Changshui Zhang, Feiping Nie∗, Shiming Xiang. A General Kernelization Framework for Learning Algorithms Based on Kernel PCA. Neurocomputing, 73(4-6):959–967, 2010.
52. Chenping Hou, Changshui Zhang, Yi Wu, Feiping Nie. Multiple View Semi-Supervised Di- mensionality Reduction. Pattern Recognition (PR), 43(3):720–730, 2010.
53. Feiping Nie, Shiming Xiang, Yun Liu, Changshui Zhang.  A General Graph-Based Semi- Supervised Learning with Novel Class Discovery. Neural Computing & Applications (NCA), 19(4): 549–555, 2010.
54. Feiping Nie, Shiming Xiang, Yangqing Jia, Changshui Zhang. Semi-Supervised Orthogonal Discriminant Analysis via Label Propagation. Pattern Recognition (PR), 42(11):2615–2627, 2009.
55. Changshui Zhang, Feiping Nie∗, Shiming Xiang, Chenping Hou. Soft Constraint Harmonic Energy Minimization for Transductive Learning and Its Two Interpretations. Neural Processing Letters (NPL), 30(2):89–102, 2009.
56. Shiming Xiang, Feiping Nie, Chunxia Zhang, Changshui Zhang. Interactive Natural Image Seg- mentation via Spline Regression. IEEE Transactions on Image Processing (TIP), 18(7):1623– 1632, 2009.
57. Chenping Hou, Feiping Nie, Changshui Zhang, Yi Wu. Learning a Subspace for Face Image Clustering via Trace Ratio Criterion.  Optical Engineering (OE), 48(6), 2009.
58. Shiming Xiang, Feiping Nie, Changshui Zhang, Chunxia Zhang. Nonlinear Dimensionality Reduction with Local Spline Embedding. IEEE Transactions on Knowledge and Data Engineering (TKDE), 21(9):1285–1298, 2009.
59. Chunxia Zhang, Shiming Xiang, Feiping Nie, Yangqiu Song. Nonlinear dimensionality reduction with relative distance comparison. Neurocomputing, 72(7-9):1719–1731, 2009.
60. Yangqing Jia, Feiping Nie, Changshui Zhang. Trace Ratio Problem Revisited. IEEE Transactions on Neural Networks (TNN), 20(4):729–735, 2009.
61. Shiming Xiang, Feiping Nie, Yangqiu Song, Changshui Zhang, Chunxia Zhang. Embedding New Data Points for Manifold Learning via Coordinate Propagation. Knowledge and Information Systems (KAIS), 19(2):159–184, 2009.
62. Chenping Hou, Feiping Nie, Changshui Zhang, Yi Wu. Learning an Orthogonal and Smooth Subspace for Image Classification. IEEE Signal Processing Letters (SPL), 16(4):303–306, 2009.
63. Feiping Nie, Shiming Xiang, Yangqiu Song, Changshui Zhang. Orthogonal Locality Minimizing Globality Maximizing Projections for Feature Extraction.  Optical Engineering (OE), 48(1), 2009.
64. Feiping Nie, Shiming Xiang, Yangqiu Song, Changshui Zhang. Extracting the Optimal Dimen- sionality for Local Tensor Discriminant Analysis. Pattern Recognition (PR), 42(1):105–114, 2009.
65. Shiming Xiang, Feiping Nie, Changshui Zhang. Learning a Mahalanobis Distance Metric for Data Clustering and Classification. Pattern Recognition (PR), 41(12):3600-3612, 2008.
66. Yangqiu Song, Feiping Nie, Changshui Zhang, Shiming Xiang. A Unified Framework for Semi- Supervised Dimensionality Reduction. Pattern Recognition (PR), 41(9):2789–2799, 2008.
67. Shiming Xiang, Feiping Nie, Yangqiu Song, Changshui Zhang. Contour Graph Based Human Tracking and Action Sequence Recognition. Pattern Recognition (PR), 41(12):3653–3664, 2008.
68. Yangqiu Song, Feiping Nie, Changshui Zhang.  Semi-Supervised Sub-Manifold Discriminant Analysis. Pattern Recognition Letters (PRL), 29(13):1806–1813, 2008.
69. Yangqiu Song, Qutang Cai, Feiping Nie, Changshui Zhang. Semi-Supervised Additive Logistic Regression: A Gradient Descent Solution. Tsinghua Science and Technology (TST), 12(6):638- 646, 2007.

Books

1. Feiping Nie, Dong Xu, Ivor Tsang, Changshui Zhang. A Flexible and Effective Linearization Method for Subspace Learning. Book chapter in Graph Embedding for Pattern Analysis, Springe, 2013.