User:Christopher G. Baker: Difference between revisions
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Christopher G. Baker was born in 1979 in Marianna, FL. He is a Ph.D. candidate in Computational Science at [http://www.fsu.edu Florida State University]. He is currently participating in an internship at [http://www.sandia.gov Sandia National Laboratories] in Albuquerque, NM, while working on his doctoral dissertation. | |||
His work at Sandia concerns high-performance, robust parallel algorithms in the [http://software.sandia.gov/trilinos Trilinos project]. Trilinos is a collection of large-scale solvers important in scientific computing (e.g., linear systems, eigenvalue problems, non-linear optimization). Baker's principal work is on Anasazi, the block eigensolvers package. | |||
His master's thesis was entitled "A Block Incremental Algorithm For Computing Dominant Singular Subspaces". This work described and analyzed a family of methods for incrementally computing low-rank approximations of a matrix, based on the truncated SVD. His dissertation concerns the optimization of smooth function defined on Riemannian manifolds. It focuses on the class of retraction-based optimization methods, particularly the Riemannian trust-region methods. | |||
Please see [http://www.scs.fsu.edu/~cbaker his home page] for more information, including a full curriculum vitae. | |||
--[[User:Christopher G. Baker|Christopher G. Baker]] 10:32, 17 May 2007 (MDT) | |||
[[Category:CZ Authors|Baker, Christopher G.]] |
Latest revision as of 02:36, 22 November 2023
The account of this former contributor was not re-activated after the server upgrade of March 2022.
Christopher G. Baker was born in 1979 in Marianna, FL. He is a Ph.D. candidate in Computational Science at Florida State University. He is currently participating in an internship at Sandia National Laboratories in Albuquerque, NM, while working on his doctoral dissertation.
His work at Sandia concerns high-performance, robust parallel algorithms in the Trilinos project. Trilinos is a collection of large-scale solvers important in scientific computing (e.g., linear systems, eigenvalue problems, non-linear optimization). Baker's principal work is on Anasazi, the block eigensolvers package.
His master's thesis was entitled "A Block Incremental Algorithm For Computing Dominant Singular Subspaces". This work described and analyzed a family of methods for incrementally computing low-rank approximations of a matrix, based on the truncated SVD. His dissertation concerns the optimization of smooth function defined on Riemannian manifolds. It focuses on the class of retraction-based optimization methods, particularly the Riemannian trust-region methods.
Please see his home page for more information, including a full curriculum vitae.
--Christopher G. Baker 10:32, 17 May 2007 (MDT)