王卫卫，西安电子科技大学教授、博士生导师。分别于1993，1998和2001年在西安电子科技大学应用数学系获得应用数学专业学士、硕士和博士学位。曾在澳大利亚悉尼大学、美国宾夕法尼亚大学、杜兰大学、新奥尔良大学、香港理工大学做访问研究。兼任陕西省计算数学学会副理事长（2014-2019）。主要研究方向：机器学习、图像处理的数学方法。主持完成国家自然科学基金面上项目2项。曾获陕西省科技奖1项。在科学出版社合作出版科研专著《图像处理的变分与偏微分方程方法》一部，在国内外重要学术期刊与会议上合作发表论文70余篇，SCI检索论文30余篇，发表期刊包括IEEE Trans. on Image Processing，IEEE Trans. On Circuits and Systems for Video Technology, SIAM J. on Multiscale Modeling and Simulation，Pattern Recognition，Signal Processing等。

                            Resume

NAME AND PRESENT POSITION

Weiwei Wang, Professor of Mathematics

E-mail    vivianwang919@126.com

RESEARCH INTERESTS

Machine learning           Subspace clustering, with applications in computer vision and bio-medical informatics

Image segmentation         active contour/level set methods, image feature clustering

Image restoration              variational methods, partial differential equations, sparse representation

EDUCATIONAL BACKGROUND

Ph.D., Applied Mathematics, Xidian University, Xi’an, China, 2001

M.S., Applied Mathematics, Xidian University, Xi’an, China, 1998

B.S., Applied Mathematics, Xidian University, Xi’an, China, 1993

HONORS
• The second prize for Science and Technology Awards of Colleges and Universities in Shaanxi Province, 2018
• The second prize for distinguished textbook “Numerical Analysis”, Xidian University, 2015;
• The first prize for high-quality teaching at Xidian University, 2014;
• The first prize for outstanding research at Xidian University, 2003.

CONTRACTS AND GRANTS
NSFC, 1/1/2009-31/12/2011, PI, Cartoon+Texture Decomposition of Images
NSFC, 1/1/2015-31/12/2011, PI, Image segmentation based on high-dimensional features and sparse subspace clustering

PUBLICATIONS
A. Books, Co-authored

X. Feng, W. Wang, Variational and PDE Methods for Image Processing, China Science Publishing&Media Ltd., (2008).

B. Selected Journal Paper

1. S. Kong, W. Wang*, X.Feng, and X. Jia, Deep RED Unfolding Network for Image Restoration, IEEE Trans.on Image Processing, vol. 31, 2022, pp.852-867.

2. W. Wang*, C. Yang, H. Chen, and X. Feng, Unified Discriminative and Coherent Semi-Supervised Subspace Clustering, IEEE Trans. On Image Processing, 2018.5, 27(5):2461-2470. 

3. H. Chen, W. Wang*, X. Feng, Structured Sparse Subspace Clustering with Within-Cluster Grouping, Pattern Recognition 83 (2018):107–118.

4. W. Wang*, B. Zhang, X. Feng, Subspace Segmentation by Correlation Adaptive Regression, IEEE Trans. On Circuits and Systems for Video Technology, 2018.10, 28(10): 2612-2621.

5. C.Yang, W.Wang*, X. Feng, Joint image restoration and edge detection in cooperative game formulation, Signal Processing, vol.191, 2022:108363.

6. W. Zhao, W. Wang*, X. Feng, Y. Han, A new variational method for selective segmentation of medical images, Signal Processing 190 (2022) :108292.

7. C. Yang, W. Wang*, X. Feng, X. Liu, Weighted l1 Method Noise Regularization for Image Deblurring, Signal Processing, 157, 2019:14-24.

8. W. Wang*, X. Feng, Anisotropic Diffusion with Nonlinear Structure Tensor, SIAM J. Multiscale modeling and simulation, 2008, 7(2):963-977.

9. C. Yang, W. Wang*, X. Feng, R. He, Group Discriminative least square regression for multicategory classification, Neurocomputing, 407(2020):175-184, 2020.5

10. H. Chen, W. Wang*, X. Feng, R. He, Discriminative and coherent subspace clustering, Neurocomputing, 284 (2018):177–186.

11. W. Wang*, C. Wu, Image Segmentation by Correlation Adaptive Weighted Regression, Neurocomputing, Dec.6, 2017, vol.267, pp.426–435.

12. W. Wang*, D. Zhai, T. Li, X. Feng, Salient edge and region aware image retargeting, Signal Processing: Image Communication, vol. 29, pp.1223–1231, 2014.8.

13. W. Wang*, P. Shui, X. Feng. Variational models for fusion and denoising of multi-focus images. IEEE signal processing letters, 2008.7, 15(1):65-68.

14. C. Yang, W. Wang*, X. Feng, Classification-Friendly Sparse Encoder and Label Transformation Learning, IEEE Access, Vol.8, pp.54494-54505, 2020.3.

15. X. Li, W. Wang*, X. Feng, et al., Image denoising via bidirectional low rank representation with cluster adaptive dictionary, IET Image Processing, 2016.10,10(12):952-961.

16. C. Wu, W. Wang*, “Image segmentation by adaptive nonconvex local and global subspace representation,” J. Electron. Imaging 25(3), 033026 (2016).

17. B. Zhang, W. Wang*, X. Feng, Subspace Clustering with Sparsity and Grouping Effect, Mathematical Problems in Engineering, March 22, 2017.

18. W. Wang*, S. Kong, A. Razi, X. Feng, Image regularity and fidelity measure with a two-modality potential function, Mathematical Problems in Engineering, Vol.2017 (2017).

19. H. Huang, C. Lu, L. Zhang, W. Wang*, Convergence and stability analysis of the half thresholding based few-view CT reconstruction, J. Inverse Ill-Posed Problems, May 31, 2020.

20. H. Huang, W. Wang*, C. Lu, X. Feng, R. He, Side-information-induced reweighted sparse subspace clustering, J. of Industrial and Management Optimization, 2019.

21. X Jia, X Feng, W. Wang, et al. Online Schatten quasi-norm minimization for robust principal component analysis, Information Sciences, 476,83-94, 2019.

22. Y. Li, Q. Zhao, X. Feng, W. Wang, R. Zhang, A. Yan, A variational image segmentation method exploring both intensity means and texture patterns, Signal Processing: Image Communication, 76:214-230, 2019.

23. X. Jia, X. Feng, W. Wang, C. Xu, L. Zhang, Bayesian inference for adaptive low rank and sparse matrix estimation, Neurocomputing , 2018.2, 291 (2018) 71–83.

24. X Jia, X Feng, W Wang, L Zhang. An extended variational image decomposition model for color image enhancement. Neurocompting.322,216-228,2018.

25. X. Jia, X. Feng, W. Wang, Rank constrained nuclear norm minimization with application to image denoising [J].  Signal Processing, 2016, 129: 1-11.

26. S. Wang, X. Feng, W. Wang. "Low-rank + Dual" Model Based Dimensionality Reduction[J]. Neurocomputing. Vol.178, pp.3-10,2016.2.

27. X. Feng, L. Luo, X. Jia, W. Wang, A-divide-and-conquer stochastic alterable direction image denoising method, Signal Processing, 108:90-101,2015.

28. X. Zhang, X. Feng, W. Wang, Two direction nonlocal model for image denoising, IEEE Trans. on Image Processing, vol.22, no.1, pp.408-412, 2013.

29. X. Zhang, X. Feng, W. Wang, W. Xue, Edge Strength Similarity for Image Quality Assessment[J]. IEEEE Signal Processing Letters, vol. 20, no.4, pp.319-322, 2013.

30. Y. Han, X. Feng, G. Baciu, W. Wang, Nonconvex sparse regularizer based speckle noise removal, Pattern Recognition, vol.46, no.3, pp.989-1001, 2013.

31. X. Zhang, X. Feng, W. Wang, G. Liu. Image Denoising via 2D dictionary learning and adaptive hard thresholding [J]. Pattern Recognition Letters, vol.34, no.16, pp.2110-2117, 2013.

32. X. Zhang, X. Feng, W. Wang, G. Liu, Two direction nonlocal model for imager interpolation[J]. SCIENCE CHINA, Technological series, vol.56, no.4, pp.930-939, 2013.

33. X. Zhang, X. Feng, W. Wang, et al., Gradient based Wienner filter for image denoising, Computers & Electrical Engineering, vol.39, no.3, pp.934-944, 2013.

34. Y. Han, W. Wang, X. Feng, A new fast multiphase image segmentation algorithm based on nonconvex regularizer, Pattern Recognition, vol.45, no. 1, pp.363-372, 2012.

35. X. Feng, G. Liu, W. Wang, Iterative regularization and inverse scale space methods with wave atoms, Applicable Analysis, vol.90, no.8, pp.1215-1225, 2011.

36. Y. Li, X. Feng, W. Wang, Color-dependent diffusion equations based on quaternion algebra, Chinese Journal of Electronics,2012, 20(2): 277-282.

37. S. Zhou, W. Wang, L. Zhou. A New Technique for Generalized Learning Vector Quantization Algorithm. Image and Vision Computing, 2006, 24(7):649-655. 

C. Selected Conference Paper

1. W. Wang*, C. Yang, Q. Li, Discriminative analysis dictionary and classifier learning for pattern classification, IEEE Inter. Conf. On Image Processing, Taibei, 2019

2. C. Yang, W. Wang*, X. Feng，Group discriminative least square regression, ISICDM2019, August 24-26, Xi’an, China, 324-329

3. Q. Wang, W. Wang*, X. Feng，Subspace clustering by relaxed block diagonal representation, ISICDM2019, August 24-26, Xi’an, China, 343-348

4. A. Razi, W. Wang*, X. Feng, Image Segmentation by Active Contour Model with a New Data Fidelity, 2017 International Conference on Machine Vision and Information Technology (CMVIT 2017), Singapore, March 16, 2017

5. A. Razi, W. Wang*, X.Feng, An Active Contour Method Using Harmonic Mean, IEEE 2016 International Conference on Signal and Image Processing (ICSIP 2016), Beijing, China, 13-15 August 2016, pp.287-291

6. X. Jia,  X Feng, W. Wang, Adaptive regularizer learning for low rank approximation with application to image denoising, [C] IEEE Inter.  Conf.  On Image Processing, 2016: 3096-3100.

7. W. Wang*, C. Wu, H. Huang, X. Feng, Subspace Clustering by weighted correlation adaptive regression, Proceedings of the 2016 International Conference on Machine Learning and Cybernetics (ICMLC2016), Jeju, South Korea, 10-13 July 2016, pp.453-458.

8. H. Chen, W. Wang*, C. ZHAO, H. Huang, Simultaneous Multiphase image segmentation and Cartoon-texture Decomposition，Proceedings of the 2016 International Conference on Wavelet Analysis and Pattern Recognition(ICWAPR2016), Jeju, South Korea, 10-13 July  2016, pp.230-235.

9. X. Li, W. Wang*, A. Razi, T. Li, Nonconvex low-rank sparse factorization for image segmentation [C]. in Proceedings of the 11th International Conference on Computational Intelligence and Security, 2015, 227-230.

10. Z. Li, W. Wang*, P. Shui, Parameter estimation and two-stage segmentation algorithm for the Chan –Vese model, IEEE Inter. Conf. On Image Processing, Atlanta, GA, USA, 8-11, Oct. 2006: 201-204.

11. W. Wang*, P. Shui, G. Song, Multifocus image fusion in wavelet domain. IEEE Inter. Conf. on Machine Learning and Cybernetics, Xi’an, 2003.11, 5:2887-2890.

12. Jing Li, Weiwei Wang*, Xiaoping Li. Image retargeting based on a new salient region detection method [C]. in Proceedings of the 11th International Conference on Computational Intelligence and Security, 2015, 179-182.

13. Tao Li, Weiwei Wang*, Xiangchu Feng, Long Xu, Image Denoising Using Low-Rank Dictionary and Sparse Representation[C] 2014 International Conference on Computational Intelligence and Security (CIS'2014), November 15-16, 2014, Kunming, Yunnan Province, China. pp.228-232.