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向 华
  ==> 个人简介

 

 

  Name: Hua XIANG

  Degree: PhD

  Major: Computational Mathematics

  Email: hxiang@whu.edu.cn

  Address: School of Mathematics and Statistics, Wuhan University,

       430072 Wuhan, P. R. China

 

  Education

  ◆  September 2003 - June 2006, Institute of Mathematics, Fudan University, Shanghai, China; PhD degree in Computational Mathematics.

  ◆  September 1999 - June 2002, Institute of Mechanics, Chinese Academy of Sciences (CAS), Beijing, China; Master degree in Fluid Mechanics.

  ◆  September 1995 - June 1999, Department of Naval Architecture and Ocean Engineering, Harbin Engineering University, Harbin, China; Bachelor degree in Shipbuilding Engineering.

 

  Job Experiences

  ◆  November 2015 – present, Professor in School of Mathematics and Statistics, Wuhan University, China.

  ◆  December 2008 – November 2015, Associate professor in School of Mathematics and Statistics, Wuhan University, China.

  ◆  July 2006 – December 2008, Assistant professor in School of Mathematics and Statistics, Wuhan University, China.

 

  Other Research Experiences

  ◆  January 2009 – December 2009, Post-doctoral researcher in Laboratoire Jacques-Louis Lions, Universite Pierre et Marie Curie (Paris VI), working on domain decomposition methods with Frederic Nataf.

  ◆  January 2007 – August 2008, Post-doctoral researcher in INRIA Saclay-Ile de France, working on parallel direct methods for dense and sparse linear systems with Laura Grigori.

 

  ◆  January – Febrary, August 2018, Visiting professor in Department of Applied Mathematics, The Hong Kong Polytechnic University. 

  ◆  July 1 – July 7, 2013, Visiting professor in Department of Mathematics, University of Macau.

  ◆  August 2012, January 2014, January 2016, Visiting professor in Department of Mathematics, The Chinese University of Hong Kong.

  ◆  January 2011 – Febrary 2011, Visiting professor in LJLL, Universite Pierre et Marie Curie, Paris.

  ◆  July 2002 – January 2003, Research assistant working with Professor Zhi Gao in the Key Laboratory of High Temperature of Gas Dynamics, Institute of Mechanics, Chinese Academy of Sciences, Beijing, China.

 

  Teaching

   Calculus, Linear algebra, Computational methods, Numerical analysis, Numerical experiments, Advanced numerical analysis, Advanced numerical linear algebra, Quantum information and quantum computations.

 

  Text Books

  H. Xiang, D. M. Li, Numerical Computing with Engineering Applications (in Chinese), Tsinghua University Press, 2015. 

  X. F. Zou, S. L. Chen, B. Q. Hu, H. Xiang, Study Guide for Numerical Analysis (in Chinese), Wuhan University Press, 2008.

 

  Research Interests

   (Numerical) Mathematics + Code + (Physical) Applications.

   Quantum Computing, Matrix Computations, Tensor analysis, Inverse Problems, Domain Decomposition Methods, Machine Learning, Numerical Relativity, etc.

 

  Preprints

  H. Wang, H. Xiang, Quantum algorithms for total least squares data fitting, submitted to Physical Letter A.

  H. Wang, H. Xiang, A quantum eigensolver for symmetric tridiagonal matrices, submitted to Quantum Information Processing.

  C. Shao, H. Xiang, Quantum regularized least squares solver with parameter estimate, arXiv:1812.09934.

  N. Wu, H. Xiang, Randomized QLP algorithm and error analysis, arXiv:1811.009334.

  X. He, H. Xiang, Singular values of Riemann curvature tensor, arXiv:1807.08437.  

  H. Xiang, L. Zhang, Randomized iterative methods with alternating projections, arXiv:1708.09845.

  H. Xiang, L. Qi, Y. Wei, On the M-eigenvalues of elasticity tensor and the strong ellipticity condition, arXiv:1708.04876.

  L. Zhang, H. Xiang, Variant of Horn's problem and derivative principle, arXiv:1707.07264.

  H. Xiang, S. Zhang, J. Zou, Preconditioners and their analyses for edge element saddle-point systems arising from time-harmonic Maxwell equations, arXiv:1610.03196.

  K. Ito, H. Xiang, J. Zou, An inexact Uzawa algorithm for generalized saddle-point problems and its convergence, arXiv:1408.5547.

 

  Peer-reviewed Journal Publications

   H. Xiang, L. Qi, Y. Wei, M-eigenvalues of the Riemann curvature tensor, Communications in Mathematical Sciences, 2018. arXiv:1802.10248.

  C. Shao, H. Xiang(*), Quantum circulant preconditioner for linear system of equations, Physical Review A 98, 062321 (2018).

   P. Xie, H. Xiang(*), Y. Wei, Randomized Algorithms for total least squares problems, Numerical Linear Algebra with Applications, 2018;e2219. https://doi.org/10.1002/nla.2219.

   A. Fan, H. Wang, H. Xiang, X. Zou, Inferring large-scale gene regulatory networks using a randomized algorithm based on singular value decomposition, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018. DOI: 10.1109/TCBB.2018.2825446.

   P. Xie, H. Xiang, Y. Wei, A contribution to perturbation analysis for total least squares problems, Numerical Algorithms, 2017, DOI 10.1007/s11075-017-0285-1.

   L. Zhang, H. Xiang, Average entropy of a subsystem over a global unitary orbit of a mixed bipartite state, Quantum Information Processing, (2017) 16:112, DOI: 10.1007/s11128-017-1570-6.

   H. Xiang, J. Zou, Randomized algorithms for large-scale inverse problems with general Tikhonov regularizations, Inverse Problems, 31 (2015), 085008 (24pp). doi:10.1088/0266-5611/31/8/085008.

   J. Demmel, L. Grigori, M. Gu, H. Xiang, Communication avoiding rank revealing QR factorization with column pivoting, SIAM Journal on Matrix Analysis and Applications, 36(1), pp 55-89, 2015. See also UCB/EECS-2013-46 and LAWN 276.

   H. Shen, H. Xiang(*), Uzawa algorithms with variable relaxation for nonsymmetric generalized saddle point problems, Numerical Linear Algebra with Applications, 22 (2015), pp.1020–1038. DOI: 10.1002/nla.1988.

   B. Liu, H. Xiang(*), An approximate linear solver in least square support vector machine using randomized singular value decomposition, Wuhan University Journal of Natural Sciences 08/2015; 20(4):283-290. DOI:10.1007/s11859-015-1094-9.

   H. Xiang, F. Nataf, Two-level algebraic domain decomposition preconditioners using Jacobi–Schwarz smoother and adaptive coarse grid corrections, Journal of Computational and Applied Mathematics, 261 (2014), pp. 1-13.

   V. Dolean, P. Jolivet, F. Nataf, N. Spillane, H. Xiang, Two-level domain decomposition methods for highly heterogeneous Darcy equations, Connections with multiscale methods, Oil & Gas Science and Technology - Rev. IFP Energies nouvelles, Vol. 69 (2014), No. 4, pp. 731-752. DOI: 10.2516/ogst/2013206.

   C. Guo, H. Xiang(*), A note on the upper bound in SA AMG convergence analysis, Numerical Linear Algebra with Applications, Volume 21, Issue 3, (2014), pp. 399–402. DOI:10.1002/nla.1879.

   H. Xiang, J. Zou, Regularization with randomized SVD for large-scale discrete inverse problems, Inverse Problems, 29 (2013), 085008(23pp), doi:10.1088/0266-5611/29/8/085008.

   P. Have, R. Masson, F. Nataf, M. Szydlarski, H. Xiang, T. Zhao, Algebraic domain decomposition methods for highly heterogeneous problems, SIAM Journal on Scientific Computing, 35 (2013), pp. C284–C302.

   H. Diao, H. Xiang, Y. Wei, Componentwise condition numbers of Sylvester and Lyapunov equations, Numerical Linear Algebra and its Applications, 19 (4), pp.639-654, 2012. DOI:10.1002/nla.790.

   L. Grigori, J. Demmel, and H. Xiang, CALU: a communication optimal LU factorization algorithm, SIAM Journal on Matrix Analysis and Applications, 32 (2011), pp. 1317-1350. See also UCB-EECS-2010-29 and LAWN226.

   Frédéric Nataf, Hua Xiang, Victorita Dolean, Nicole Spillane, A coarse space construction based on local Dirichlet-to-Neumann maps, SIAM J. Sci. Comput., 33 (2011), pp. 1623-1642.

   Frederic Nataf, Hua Xiang, Victorita Dolean, A two level domain decomposition preconditioner based on local Dirichlet-to-Neumann maps, C. R. Acad. Sci. Paris, Ser. I, 348 (2010), pp. 1163-1167.

   Hua Xiang, Laura Grigori, Kronecker product approximation preconditioners for convection–diffusion model problems, Numer. Linear Algebra Appl., (17) 2010, pp. 691–712.

   Laura Grigori, Desire Nuentsa Wakamb, Hua Xiang (*), Saving flops in LU based shift-and-invert strategy, Journal of Computational and Applied Mathematics, 234 (2010), pp. 3216–3225.

   L. Grigori, J. Demmel, H. Xiang, Communication avoiding Gaussian elimination, SC’08, Proceedings of the 2008 ACM/IEEE conference on Supercomputing, 2008, pp.1-12.

   W. Kang, H. Xiang, Level-2 condition numbers for least squares solution of Kronecker product linear systems, International Journal of Computer Mathematics, 85(2008), pp. 827-841.

   H. Xiang, Y. Wei, On normwise structured backward errors for saddle point systems, SIAM Journal on Matrix Analysis and Applications, 29(2007), pp. 838-849.

   H. Xiang, Y. Wei, Structured mixed and componentwise condition numbers of some structured matrices, Journal of Computational Applied Mathematics, 202(2007), pp. 217-229.

   H. Zhang, H. Xiang, Y. Wei, Condition numbers for linear systems and Kronecker product linear systems with multiple right-hand sides, International Journal of Computer Mathematics, 84(2007), pp. 1805-1817.

   H. Xiang, Y. Wei, H. Diao, Perturbation analysis of generalized saddle point systems, Linear Algebra and its Applications, 419(2006), pp. 8-23.

   H. Xiang, A note on minimax representation for subspace distance and singular values, Linear Algebra and its Applications, 414(2006), pp. 470-473.

   Q. Liu, H. Xiang, V. P. Singh, A simulation model for unified interrill erosion and rill erosion on hillslopes, Hydrological Processes, 2006, 20(3), pp. 469-486.

   W. Kang, H. Xiang, Condition numbers with their condition numbers for the weighted Moore-Penrose inverse and the weighted least squares solution, J. Appl. Math. & Computing, 22(2006), pp. 95-112.

   Q. Liu, V. P. Singh, H. Xiang, Plot Erosion Model Using Gray Relational Analysis Method, J. Hydrologic Engineering, 2005, 10(4), pp. 288-294.

   H. Xiang, H. Diao, Y. Wei, On the perturbation bounds of Kronecker product linear systems and their level-2 condition numbers, Journal of Computational Applied Mathematics, 183 (2005), pp. 210-231.

   Y. Wei, Y. Cao, H. Xiang, A note on the componentwise perturbation bounds of matrix inverse and linear systems, Applied Mathematics and Computation, 169 (2005), pp. 1221-1236.

   Q. Liu, J. Li, L. Chen, H. Xiang, Overland flow and soil erosion dynamics (II): Soil erosion, Advances in Mechanics, 2004, 34(4), pp. 493-506 (in Chinese).

   Q. Liu, J. Li, L. Chen, H. Xiang, Overland flow and soil erosion dynamics (I): Overland flow, Advances in Mechanics, 2004, 34 (3), pp. 360-372 (in Chinese).

   Z. Gao, H. Xiang, Y. Shen, Perturbation finite volume method and high precision reconstruction, Computational Physics, 2004, 21(2), pp. 131-136 (in Chinese).

   H. Xiang, Q. Liu, J. Li, Influences of Slope Surface Conditions on the Runoff Generation, Journal of Hydrodynamics, series A, 2004, 19(6), pp. 774-782 (in Chinese).

 

  International Conferences

  ◆ Communication-avoiding matrix algorithms using tournament pivoting (joint work with James W. Demmel, Laura Grigori, and Ming Gu), A poster on the 5th International Conference on Numerical Algebra and Scientific Computing (NASC 2014), Tongji University, Shanghai, P.R. China, October 25-29, 2014.

  ◆ A communication optimal LU decomposition, May 3 - 14, 2010, CIMPA UNESCO Thematic School, Wuhan, P. R. China (invited speaker).

  ◆ Parallel sparse LU factorization with communication avoiding pivoting strategy, a talk given in the seminar at RICAM (Johann Radon Institute for Computational and Applied Mathematics, Austrian Academy of Sciences), July 22, 2008, Linz, Austria.

  ◆ A low latency approach for parallel sparse LU factorization, SIAM Conference on Parallel Processing for Scientific Computing (PP08), March 12-14, 2008, Atlanta, Georgia, USA.

  ◆ Communication avoiding dense QR and LU decompositions, Matrix Analysis and Applications (M2A07, in honor of Gérard Meurant for his 60th birthday), October 15-19, 2007, CIRM Luminy, Marseille, France, presented by L. Grigori.

  ◆ Kronecker product approximation preconditioner for convection-diffusion model problems, 2007 International Conference on Preconditioning Techniques for Large Sparse Matrix Problems in Scientific and Industrial Applications, July 9-12, 2007, Météopole, Toulouse, France.

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