ZHANG, Yin
Presidential Chair Professor
Ph.D. Applied Mathematics, Stony Brook University, 1987
B.S. Environmental Engineering, Chongqing University, 1977
Prof. Yin Zhang is currently a Presidential Chair professor in the School of Data Science at The Chinese University of Hong Kong, Shenzhen and Professor Emeritus at Rice University. He graduated from Chongqing Institute of Architecture and Engineering (now Chongqing University) in 1977 and received his PhD degree in Applied Mathematics from The State University of New York (SUNY) at Stony Brook in 1987. He was a postdoctoral fellow at Rice University and an assistant professor at the University of Maryland Baltimore County. From 1996 to 2021, he worked as an associate and then full professor in the Department of Computational and Applied Mathematics at Rice University. His research focuses on optimization algorithms, software and applications with major contributions to the advancement of interior-point methodology and software, and algorithms in signal and image processing including in sparse optimization. He is a SIAM Fellow and served on various editorial boards of journals in the areas of optimization and computational mathematics, including SIAM Journal on Optimization and Mathematical Programming Computation. Recently, he received the Paul Y. Tseng Memorial Lectureship in Continuous Optimization Prize from the Mathematical Optimization Society.
1. Lijun Xu, Bo Yu and Yin Zhang. An Alternating Direction and Projection Algorithm for Structure-enforced Matrix Factorization. Computational Optimization and Applications (2017). First Online: 24 April, 2017. doi: 10.1007/s10589-017-9913-x.
2. Zaiwen Wen and Yin Zhang. Accelerating Convergence by Augmented Rayleigh-Ritz Projections For Large-Scale Eigenpair Computation. SIAM Journal on Matrix Analysis and Applications. Vol. 38-2, pp. 273-296. 2017.
3. Junyu Zhang, Zaiwen Wen and Yin Zhang. Subspace Methods With Local Refinements for Eigenvalue Computation Using Low-Rank Tensor-Train Format. Journal of Scientific Computing (First online 2016). doi: 10.1007/s10915-016-0255-0. February 2017, Volume 70, Issue 2, pp. 478-499.
4. Zaiwen Wen, Chao Yang, Xin Liu and Yin Zhang. Trace-Penalty Minimization for Large-scale Eigenspace Computation. Journal of Scientific Computing. March 2016, Volume 66, Issue 3, pp. 1175-1203.
5. Xin Liu, Zaiwen Wen and Yin Zhang. An Efficient Gauss-Newton Algorithm for Symmetric Low-Rank Product Matrix Approximations. SIAM Journal on Optimization. 25-3 (2015), pp. 1571-1608. http://dx.doi.org/10.1137/140971464.
6. Yuan Shen, Zaiwen Wen, and Yin Zhang. Augmented Lagrangian Alternating Direction Method for Matrix Separation Based on Low-Rank Factorization. Optimization Methods and Software. Vol. 29 (2), pp. 239-263. 2014.
7. Yin Zhang. Theory of Compressive Sensing via L1-Minimization: A Non-RIP Analysis and Extensions. Journal of the Operations Research Society of China. Vol. 1, Issue 1, pp. 79-105. 2013.
8. Junfeng Yang and Yin Zhang, Alternating direction algorithms for L1-problems in compressive sensing. SIAM Journal on scientific computing. 33(1), 250-278. 2011.
9. Yilun Wang, Junfeng Yang, Wotao Yin and Yin Zhang. A new alternating minimization algorithm for total variation image reconstruction. SIAM Journal on Imaging Sciences. 1(3), 248-272. 2008.
10. Elaine T. Hale, Wotao Yin and Yin Zhang. Fixed-point continuation for L1-minimization: Methodology and convergence. SIAM Journal on Optimization. 19 (3), 1107-1130. 2008.
11. Renato Monteiro and Y Zhang. A unified analysis for a class of long-step primal-dual path-following interior-point algorithms for semidefinite programming. Mathematical Programming, Series A.81 (3), 281-299. 1998.
12. Yin Zhang. Solving large-scale linear programs by interior-point methods under the MATLAB environment. Optimization Methods and Software. 10 (1), 1-31. 1998.
13. Amer El-Bakry, Richard Tapia, T Tsuchiya and Yin Zhang. On the formulation and theory of the Newton interior-point method for nonlinear programming. Journal of Optimization Theory and Applications. 89 (3), 507-541. 1996.
14. Yin Zhang. On the convergence of a class of infeasible interior-point methods for the horizontal linear complementarity problem. SIAM Journal on Optimization. 4 (1), 208-227. 1994.
15. Yin Zhang, Richard Tapia, and John Dennis. On the superlinear and quadratic convergence of primal-dual interior point linear programming algorithms. SIAM Journal on Optimization. 2 (2), 304-324. 1992.