教育经历：
2001年9月-2004年8月 香港中文大学数学系 博士
1998年9月-2001年7月 青岛海洋大学应用数学系 硕士
1996年9月-1998年7月 烟台师范学院数学系 学士
1994年9月-1996年7月 聊城师范学院数学系 大专
工作经历：
2008年8月-至今 加拿大28预测在线预测可刮奖 教授
2005年12月-2008年7月 加拿大28预测在线预测可刮奖 副教授
2004年10月-2005年10月 新加坡国立大学数学系 博士后
研究方向：
数值代数、特征值问题及其反问题、黎曼流形上的优化算法及应用
著作：
黎景辉,白正简,周国晖,高等线性代数学,高等教育出版社,2014.
授课情况：
2022-23春季学期：《线性代数I》
2023-24春季学期：《线性代数I》
获奖：
2009年度福建省科学技术奖二等奖
主持项目：
2024.01-2027.12 国家自然科学基金面上项目 （项目批准号：12371382）
2021.11-2024.11 福建省自然科学基金面上项目（项目批准号：2021J01033）
2017.01-2020.12 国家自然科学基金面上项目 （项目批准号：11671337）
论文：
G. Y. Xiao, S. Q. Zhang, and Z. J. Bai, Scaled proximal gradient methods for sparse optimization problems, J. Sci. Comput., 98 (2024) 2.
Z. Zhao, T. T. Yao, Z. J. Bai, and X. Q. Jin, A Riemannian inexact Newton dogleg method for constructing a symmetric nonnegative matrix with prescribed spectrum, Numer. Algorithms, 92 (2023), pp. 1951-1981.
G. Y. Xiao, Z. J. Bai, and W. K. Ching, A columnwise update algorithm for sparse stochastic matrix factorization, SIAM J. Matrix Anal. Appl., 43 (2022), pp. 1712-1735.
H. Ren, R. R. Ma, Q. H. Liu, and Z. J. Bai, Randomized quaternion QLP decomposition for low-rank approximation, J. Sci. Comput., 92 (2022) 80.
Z. J. Bai, H. A. Diao, H. Y. Liu, and Q. L. Meng, Stable determination of an elastic medium scatterer by a single far-field measurement and beyond, Calc. Var. Partial Differential Equations, 61 (2022) 170.
G. Y. Xiao and Z. J. Bai, A geometric proximal gradient method for sparse least squares regression with probabilistic simplex constraint, J. Sci. Comput., 92 (2022) 22.
Q. L. Meng, Z.-J. Bai, H. A. Diao, and H. Y. Liu, Effective medium theory for embedded obstacles in elasticity with applications to inverse problems, SIAM J. Appl. Math., 82 (2022), pp. 720-749.
W. W. Xu, M. K. Ng, and Z. J. Bai, Geometric inexact Newton method for generalized singular values of Grassmann matrix pair, SIAM J. Matrix Anal. Appl., 43 (2022), pp. 535-560.
M. Lu and Z. J. Bai, A receptance-based optimization approach for minimum norm and robust partial quadratic eigenvalue assignment, CSIAM Trans. Appl. Math., 2 (2021), pp. 357-375.
H. J. Gao, Z.-J. Bai, W. G. Gao, and S. Q. Zhang, Penalized-regression-based bicluster localization, Pattern Recognition, 117 (2021) 107984.
Q. L. Meng, H. A. Diao, and Z. J. Bai, Condition numbers for the truncated total least squares problem and their estimations, Numer. Linear Algebra Appl., 28 (2021) e2369.
R. R. Ma and Z. J. Bai, A Riemannian inexact Newton-CG method for stochastic inverse singular value problems, Numer. Linear Algebra Appl., 28 (2021) e2336.
Y. Wang, Z. Zhao, and Z. J. Bai, Riemannian Newton-CG methods for constructing a positive doubly stochastic matrix from spectral data, Inverse Problems, 36 (11) (2020) 115006.
T. T. Yao, Z. J. Bai, X. Q. Jin, and Z. Zhao, A geometric Gauss-Newton method for least squares inverse eigenvalue problems, BIT, 60 (2020), pp. 825-852.
Y. F. Cai, Z. G. Jia, and Z. J. Bai, Perturbation analysis of an eigenvector-dependent nonlinear eigenvalue problem with applications, BIT, 60 (2020), pp. 1-29.
R. R. Ma and Z. J. Bai, A structure-preserving one-sided Jacobi method for computing the SVD of a quaternion matrix, Appl. Numer. Math., 147 (2020), pp. 101-117.
T. T. Yao, Z. J. Bai, and Z. Zhao, A Riemannian variant of the Fletcher-Reeves conjugate gradient method for stochastic inverse eigenvalue problems with partial eigendata, Numer. Linear Algebra Appl., 26 (2019) e2221.
Z. Zhao, Z. J. Bai, and X. Q. Jin, A Riemannian inexact Newton-CG method for constructing a nonnegative matrix with prescribed realizable spectrum, Numer. Math., 140 (2018), pp 827-855.
Z. J. Bai, M. Lu, and Q. Y. Wan, Minimum norm partial quadratic eigenvalue assignment for vibrating structures using receptances and system matrices, Mech. Syst. Signal Process., 112 (2018), pp. 265-279.
Z. J. Bai and Q. Y. Wan, Partial quadratic eigenvalue assignment in vibrating structures using receptances and system matrices, Mech. Syst. Signal Process., 88 (2017), pp. 290-301.
Z. Zhao, X. Q. Jin, and Z. J. Bai, A geometric nonlinear conjugate gradient method for stochastic inverse eigenvalue problems, SIAM J. Numer. Anal., 54 (2016), pp. 2015-2035.
T. T. Yao, Z. J. Bai, Z. Zhao, and W. K. Ching, A Riemannian Fletcher-Reeves conjugate gradient method for doubly stochastic inverse eigenvalue problems, SIAM J. Matrix Anal. Appl., 37 (2016), pp. 215-234.
Z. Zhao, Z. J. Bai, and X. Q. Jin, A Riemannian Newton algorithm for nonlinear eigenvalue problems, SIAM J. Matrix Anal. Appl., 36 (2015), pp. 752-774.
学生培养：
已培养博士研究生8名，硕士研究生8名。现有硕士研究生2名
