1. Junhui Shen, Aaron J. Davis, Ding Lu and Zhaojun Bai, Hidden convexity of fair PCA and fast solver via eigenvalue optimization, arXiv:2503.00299, March, 2025

2. Nian Shao, Wenbin Chen and Zhaojun Bai, EPIC: a provable accelerated eigensolver based on preconditioning and implicity convexity SIAM J. Matrix. Anal. Appl. Vol.46, No.1, pp.45-73, 2025 (preprint)

3. Tianyi Lu, Yangfeng Su and Zhaojun Bai, Variational characterization and Rayleigh quotient iteration of 2D eigenvalue problem with Applications, SIAM J. Matrix. Anal. Appl. Vol.45, No.3, pp.1455-1468, 2024 (preprint)
   

   Yangfeng Su, Tianyi Lu and Zhaojun Bai, 2D eigenvalue problems I: existence and number of solutions, preprint on arXiv, 2019.
   Tiangyi Lu, Yangfeng Su and Zhaojun Bai, 2D eigenvalue problems II: Rayleigh quotient iteration and applications , preprint on arXiv, 2022.
   Tiangyi Lu, Yangfeng Su and Zhaojun Bai, 2D eigenvalue problems III: convergence analysis of the 2D Rayleigh quotient iteration, preprint on arXiv, 2023.
   

4. Zhaojun Bai and Ding Lu, Variational characterization of monotone nonlinear eigenvector problems and geometry of self-consistent-field iteration, SIAM J. Matrix. Anal. Appl. Vol.45, No.1, pp.84-111, 2024 https://doi.org/10.1137/22M1525326 . (preprint, 2022)

5. Dong Min Roh and Zhaojun Bai, A self-consistent field solution for robust common spatial pattern analysis, arXiv:2311.13004, Nov. 2023

6. Ming Zhou, Zhaojun Bai, Yunfeng Cai and Klaus Neymeyr, Convergence analysis of a block preconditioned steepest descent eigensolver with implicit deflation, Numer Linear Algebra and Appl. 2023; 30:e2498, https://doi.org/10.1002/nla.2498 (preprint)

7. Ji Wang, Ding Lu, Ian Davidson and Zhaojun Bai, Scalable spectral clustering with group fairness constraints, Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:6613-6629, 2023. (preprint)

8. Dong Min Roh, Zhaojun Bai and Ren-Cang Li, A bi-level nonlinear eigenvector algorithm for Wasserstein discriminant analysis , preprint, 2022.

9. Zhaojun Bai, Ren-Cang Li and Ding Lu, Sharp estimation of convergence rate of self-consistent-field iteration to solve eigenvector-dependent nonlinear eigenvalue problems, SIAM J. Matrix Anal. Appl. Vol.43, No.1, pp.301-327, 2022 (https://arxiv.org/abs/2009.09022) (preprint)

10. Lei-Hong Zhang, Li Wang, Zhaojun Bai and Ren-Cang Li, A self-consistent-field iteration for orthogonal canonical correlation analysis, IEEE Trans. Pattern Anaysis and Machine Intelligence, Vol.44, No.2, 890-904, 2022 (https://doi.org/10.1109/TPAMI.2020.3012541) (preprint)

11. Chao-Ping Lin, Ding Lu and Zhaojun Bai, Backward stability of explicit external deflation for the symmetric eigenvalue problems, arXiv:2005.01298v1, 2021

12. Chao-Ping Lin, Huiqing Xie, Roger Grimes and Zhaojun Bai, On the shift-invert Lanczos method for the buckling eigenvalue problems, International Journal of Numerical Methods in Engineering, Vol.122, No.11, 2751-2769, 2021 (https://doi.org/10.1002/nme.6640) (preprint)

13. Yunshen Zhou, Zhaojun Bai and Ren-Cang Li, Linear constrained Rayleigh quotient optimization: theory and algorithms, CSIAM Trans. Appl. Math., 2(2), pp.195-262, 2021 (preprint)

1. Arman Ahmadi, Andre Daccache, Minxue He, Peyman Namadi, Alireza Ghaderi Bafti, Prabhjot Sandhu, Zhaojun Bai, Richard L. Snyder and Tariq Kadir, Enhancing the accuracy and generalizability of reference evapotranspiration forecasting in California using deep global learning Journal of Hydrology: Regional Studies, Vol.59, June 2025, 102339 (preprint)

2. Siyu Qi, Minxue He, Raymond Hoang, Yu Zhou, Peyman Namadi, Bradley Tom, Prabhjot Sandhu, Zhaojun Bai, Francis Chung, Zhi Ding, Jamie Anderson, Dong Min Roh and Vincent Huynh, Salinity modeling using deep learning with data augmentation and transfer learning. Water 2023, 15, 2482, https://doi.org/10.3390/w15132482 (preprint)

3. Dong Min Roh, Minxue He, Zhaojun Bai, Prabhjot Sandhu, Francis Chung, Zhi Ding, Siyu Qi, Yu Zhou, Raymond Hoang, Peyman Namadi, Bradley Tom and Jamie Anderson, Physics-informed neural networks-based salinity modeling in the Sacramento-San Joaquin Delta of California. Water 2023, 15, 2320, https://doi.org/10.3390/w15132320 (preprint)

4. Siyu Qi, Minxue He, Zhaojun Bai, Zhi Ding, Prabhjot Sandhu, Francis Chung, Peyman Namadi, Yu Zhou, Raymond Hoang, Bradley Tom, Jamie Anderson and Dong Min Roh, Novel Salinity Modeling Using Deep Learning for the Sacramento-San Joaquin Delta of California, Water 2022, 14, 3624; https://doi.org/10.3390/w14223628 (preprint)

5. Siyu Qi, Minxue He, Zhaojun Bai, Zhi Ding, Prabhjot Sandhu, Yu Zhou, Peyman Namadi, Bradley Tom, Raymond Hoang and Jamie Anderson, Multi-Location Emulation of a Process-Based Salinity Model Using Machine Learning, Water 2022, 14(13), 2030; doi:10.3390/w14132030 (preprint)

6. Siyu Qi, Zhaojun Bai, Zhi Ding, Nimal Jayasundara, Minxue He, Prabhjot Sandhu, Sanjaya Seneviratne and Tariq Kadir, Enhanced artificial neural networks for salinity estimation and forecasting in the Sacramento-San Joaquin Delta of California, J of Water Resources Planning and Management, 147(10), 04021069, 2021. (preprint)

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