个人简介
Chao Yang received his Ph.D in computational mathematics from Rice Universisty in 1998. He worked at NEC Systems Lab, Inc, a subsidiary of NEC from 1998 to 1999. He was awarded the 1999 Householder fellow in scientific computing by Oak Ridge National Laboratory.
研究领域
He joined Lawrence Berkeley National Laboratory in 2000, and is currently a senior scientist. His research interests include:
developing numerical algorithms and fast implementation to accelerate scientific simulations
developing efficient and robust algorithms and implementations for solving inverse problems
His core expertise is in numerical linear algebra, optimization, large-scale data analysis and high performance computing. Over the last several years, he has successfully used techniques developed in these areas to solve problems in electronic structure calcuations, nuclear structure calculations, cavity design for accelerator models, single-particle analysis for cryo-electron microscopy, single molecular diffractive imaging, phase retrieval, ptychography etc.
近期论文
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E. Vecharynski and C. Yang, "Preconditioned iterative methods for eigenvalue counts", Lecture Notes in Computational Science, January 1, 2017,
M. Jacquelin, L. Lin and C. Yang, "A Distributed Memory Parallel Algorithm for Selected Inversion: the non-symmetric case", PMAA, December 30, 2016,
Hasan Metin Aktulga, Md. Afibuzzaman, Samuel Williams, Aydın Buluc, Meiyue… more authors » "A High Performance Block Eigensolver for Nuclear Configuration Interaction Calculations", IEEE Transactions on Parallel and Distributed Systems (TPDS), November 2016, doi: 10.1109/TPDS.2016.2630699
A. S. Banerjee, L. Lin, W. Hu, C. Yang and J. E. Pask, "Chebyshev polynomial filtered subspace iteration in the discontinuous Galerkin method for large-scale electronic structure calculations", Journal of Chemical Physics, October 1, 2016,
R. Li, Y. Xi, E. Vecharynski, C. Yang, and Y. Saad, "A Thick-Restart Lanczos algorithm with polynomial filtering for Hermitian eigenvalue problems", SIAM Journal on Scientific Computing, Vol. 38, Issue 4, pp. A2512–A2534, 2016, doi: 10.1137/15M1054493
Fabien Bruneval, Tonatiuh Rangel, Samia M. Hamed, Meiyue Shao, Chao Yang, Jeffrey B. Neaton, "MOLGW 1: many-body perturbation theory software for atoms, molecules, and clusters", Computer Physics Communications, 2016, 208:149–161, doi: 10.1016/j.cpc.2016.06.019
Meiyue Shao, Lin Lin, Chao Yang, Fang Liu, Felipe H. da Jornada, Jack… more authors » "Low rank approximation in G0W0 calculations", Science China Mathematics, June 4, 2016, 59:1593–1612, doi: 10.1007/s11425-016-0296-x
M. Jacquelin, L. Lin, W. Jia, Y. Zhao and C. Yang, "A Left-looking selected inversion algorithm and task parallelism on shared memory systems", April 9, 2016,
J. R. Jones, F.-H. Rouet, K. V. Lawler, E. Vecharynski, K. Z. Ibrahim, S.… more authors » "An efficient basis set representation for calculating electrons in molecules", Journal of Molecular Physics, 2016, doi: 10.1080/00268976.2016.1176262
Z. Wen, C. Yang, X. Liu and Y. Zhang, "A Penalty-based Trace Minimization Method for Large-scale Eigenspace Computation", J. Sci. Comp., March 1, 2016, 66:1175-1203, doi: 10.1007/s10915-015-0061-0
E. Vecharynski, C. Yang, and F. Xue, "Generalized preconditioned locally harmonic residual method for non-Hermitian eigenproblems", SIAM Journal on Scientific Computing, Vol. 38, No. 1, pp. A500–A527, 2016, doi: 10.1137/15M1027413
Wei Hu, Lin Lin, Chao Yang, Jun Dai and Jinlong Yang, "Edge-Modi
ed Phosphorene Nano ake Heterojunctions as Highly E
cient Solar Cells", Nano Lett, February 5, 2016, 16:1675–1682, doi: 10.1021/acs.nanolett.5b04593
L. Lin, Y. Saad and C. Yang, "Approximating spectral densities of large matrices", SIAM Review, February 1, 2016, 58:34–65, doi: 10.1137/130934283
P. Li, X. Liu, M. Chen, P. Lin, X. Ren, L. Lin, C. Yang, L. He, "Large-scale ab initio simulations based on systematically improvable atomic basis", Computational Materials Science, February 1, 2016, 112:503–517, doi: doi:10.1016/j.commatsci.2015.07.004
J. Brabec, C. Yang, E. Epifanovsky, A.I. Krylov, and E. Ng, "Reduced-cost sparsity-exploiting algorithm for solving coupled-cluster equations", Journal of Computational Chemistry, January 24, 2016, 37:1059–1067, doi: 10.1002/jcc.24293