特别副研究员

当前位置: 巫文婷

巫文婷

个人简介

Personal Information


Name:  Wen-Ting Wu (巫文婷)

Institute:  School of Mathematics and Statistics, Beijing Institute of Technology

Address:  No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, P.R. China

Email:  wuwenting@bit.edu.cn


Research Interests


Numerical algebra & Scientific computing

► Randomized iteration methods

Large-scale systems of linear equations

Eigenvalue problems


Education


Sep. 2014 - Jun. 2019, Ph.D. in Computational Mathematics,

Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing (China).

Supervisor: Prof. Zhong-Zhi Bai.   Major: numerical algebra.

► Sep. 2010 - Jun. 2014, Bachelor in Information and Computing Sciences, 

School of Mathematical Sciences, Dalian University of Technology, Dalian (China). 


Employment


► Aug. 2019 - Present, Assistant Professor, 

School of Mathematics and Statistics, Beijing Institute of Technology, Beijing (China).


Awards, Honors and Recognitions


► The Applied Numerical Algebra Prize, Chinese Computational Mathematical Society, Oct. 2019.


Research Grants


►01/2021 - 12/2023, National Natural Science Foundation of China (NSFC) (Grant No. 12001043), Principal Investigator.

►01/2021 - 12/2024, National Natural Science Foundation of China (NSFC) (Grant No. 12071472), Participant.


Professional Activities


►Editorial board, Numerical Linear Algebra with Applications, 2021 - present.


Publications


[1] Z.-Z. Bai and W.-T. Wu, On greedy randomized Kaczmarz method for solving large sparse linear systems, SIAM J. Sci. Comput., 40(2018), A592-A606.

[2] Z.-Z. Bai and W.-T. Wu, On relaxed greedy randomized Kaczmarz methods for solving large sparse linear systems, Appl. Math. Lett., 83(2018), 21-26.

[3] Z.-Z. Bai and W.-T. Wu, On convergence rate of the randomized Kaczmarz method, Linear Algebra Appl., 553(2018), 252-269.

[4] Z.-Z. Bai and W.-T. Wu, On greedy randomized coordinate descent methods for solving large linear least-squares problems, Numer. Linear Algebra Appl., 26(2019), e2237, pp. 1-15.

[5] W.-T. Wu, On minimization of upper bound for the convergence rate of the QHSS iteration method, Commun. Appl. Math. Comput., 1(2019), 263-282.

[6] Z.-Z. Bai and W.-T. Wu, On partially randomized extended Kaczmarz method for solving large sparse overdetermined inconsistent linear systems, Linear Algebra Appl., 578(2019), 225-250.

[7] Z.-Z. Bai, L. Wang and W.-T. Wu, On convergence rate of the randomized Gauss-Seidel method, Linear Algebra Appl., 611(2021), 237–252.

[8] Z.-Z. Bai, W.-T. Wu and G.V. Muratova, The power method and beyond, Appl. Numer. Math., 164(2021), 29-42.

[9] Z.-Z. Bai and W.-T. Wu, On refinement of the generalized Bendixson theorem, Appl. Numer. Math., 164(2021), 125–138.

[10] C.-Q. Miao and W.-T. WuOn relaxed filtered Krylov subspace method for non-symmetric eigenvalue problems, J. Comput. Appl. Math., 398(2021), 113698, 15 pp.

[11] W.-T. Wu, On two-subspace randomized extended Kaczmarz method for solving large linear least-squares problems, Numer. Algorithms, (2021), DOI: https://doi.org/10.1007/s11075-021-01104-x.