|Tamara G. Kolda|
Tamara (Tammy) Kolda is a Distinguished Member of Technical Staff in the Informatics and Systems Assessments department at Sandia National Laboratories in Livermore, California. Her current research interests include network modeling and analysis, multilinear algebra and tensor decompositions, and compressed sensing. She has also worked in data mining, optimization, nonlinear solvers, graph algorithms, cybersecurity, parallel computing and the design of scientific software. Before joining Sandia, Tammy held the Householder Postdoctoral Fellowship in Scientific Computing at Oak Ridge National Laboratory. She received her Ph.D. in applied mathematics from the University of Maryland at College Park in 1997. She has received several awards, most notably a 2003 Presidential Early Career Award for Scientists and Engineers (PECASE). She was a keynote speaker at several workshops and conferences, including the 2010 SIAM Annual Meeting and the 2007 IEEE International Conference on Data Mining (ICDM'07).
In network modeling and analysis, Tammy is leading a DARPA-sponsored project on Fast algorithms for Evolving graphs via Assays, Sampling, & Theory. A major focus of the effort is designing scalable network models that reproduce characteristics of real-world networks. One such model is the BTER model. Tammy is also involved in analyzing existing models such as Stochastic Kronecker Graphs (SKG; aka R-MAT) and scalable methods for measuring large-scale network characteristics. Tammy will presented a plenary talk on graph models at the 2013 SIAM CS&E conference.
In multilinear algebra and tensor decompositions, Tammy is best known for her work on the MATLAB Tensor Toolbox and a SIAM Review article on tensor decompositions and applications. She co-authored a paper on memory-efficient Tucker (MET) tensor decompositions that resulted in the Best Paper Prize in the Theoretical/Algorithms Category at the 2008 IEEE International Conference on Data Mining (ICDM'08). In 2009, Tamara was recognized with a Sandia Award for Excellence for Laboratory Directed Research & Development for work related to tensor decompositions.
In past work, Tammy oversaw the development of HOPSPACK, a serial, multithreaded, or parallel, derivative-free optimization software framework for efficiently solving nonlinear optimization problems; this new software extends and succeeds her well-known APPSPACK software package. See her SIAM Review article on direct search methods for more information on derivative-free search. Additionally, Tammy was a contributor to the Trilinos project, a suite of numerical software packages and winner of a 2004 R&D 100 award, and co-lead on the NOX nonlinear solver C++ software package, which is part of Trilinos. Tammy has also worked in the area of graph partitioning, considering the problem of partitioning matrices for parallel computing. Tammy's thesis work considered the semi-discrete matrix decomposition (SDD) as applied to latent semantic indexing in text retrieval as well as variations on the well-known limited-memory BFGS methods in optimization.
Currently, Tammy serves on the SIAM Board of Trustees, is the Section Editor for the Software and High Performance Computing section of the SIAM Journal on Scientific Computing, is an Editor for the newly formed Journal on Complex Networks (Oxford University Press), and is an Associate Editor for SIAM Journal on Matrix Analysis. She is also Editor-in-Chief for a SISC Special Issue on Planet Earth and Big Data. She regularly serves on program committees and was co-chair for the 2008 SIAM Annual Meeting; served as the Chair, Vice Chair and Secretary of the SIAM Activity Group on Computational Science and Engineering from 2009-2010, 2007-2008 and 2004-2006, respectively; served as Secretary of the SIAM Activity Group on Linear Algebra from 2001-2003; edited NA Digest from 2005-2010; served as a member of the human resources board for the American Institute of Mathematics; and was Web Editor for the Association for Women in Mathematics from 1997-2002. Tammy is also a Distinguished Member of the Association for Computing Machinery (ACM).