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Tamara G. Kolda

From Wikipedia, the free encyclopedia
Tamara G. Kolda
Alma materUniversity of Maryland Baltimore County
University of Maryland College Park
Awards
Scientific career
FieldsApplied mathematics
Computational science
InstitutionsOak Ridge National Laboratory
Sandia National Laboratories
Thesis Limited-Memory Matrix Methods With Applications  (1997)
Doctoral advisorDianne P. O'Leary

Tamara G. Kolda is an American applied mathematician and former Distinguished Member of Technical Staff at Sandia National Laboratories. She is noted for her contributions in computational science, multilinear algebra, data mining, graph algorithms, mathematical optimization, parallel computing, and software engineering.[2][3]

Education

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Kolda received her bachelor's degree in mathematics in 1992 from the University of Maryland Baltimore County and her PhD in applied mathematics from the University of Maryland College Park in 1997.[4]

Career and research

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Kolda was a Householder Postdoctoral Fellow at Oak Ridge National Laboratory from 1997 to 1999 before joining Sandia National Laboratories.

Awards and honors

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Kolda received a Presidential Early Career Award for Scientists and Engineers in 2003, best paper prizes at the 2008 IEEE International Conference on Data Mining and the 2013 SIAM International Conference on Data Mining, and has been a distinguished member of the Association for Computing Machinery since 2011.[2][5] She was elected a Fellow of the Society for Industrial and Applied Mathematics in 2015.[6] She was elected a Fellow of the Association for Computing Machinery in 2019 for "innovations in algorithms for tensor decompositions, contributions to data science, and community leadership."[1] She was elected to the National Academy of Engineering in 2020, for "contributions to the design of scientific software, including tensor decompositions and multilinear algebra".[7]

References

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  1. ^ a b "Tamara G Kolda". awards.acm.org.
  2. ^ a b Camacho-Lopez, Tara (23 June 2015). "Sandian Named Fellow of the Society for Industrial and Applied Mathematics". Sandia Energy.
  3. ^ "SC16 Invited Talk Spotlight: Dr. Tamara G. Kolda Presents "Parallel Multiway Methods for Compression of Massive Data and Other Applications"". SuperComputing16. 29 September 2016. Retrieved 15 October 2017.
  4. ^ "Tamara G. Kolda - CV" (PDF).
  5. ^ "Tamara G Kolda". awards.acm.org.
  6. ^ "SIAM Fellows Class of 2015". fellows.siam.org.
  7. ^ "National Academy of Engineering Elects 86 Members and 18 International Members". National Academy of Engineering. February 6, 2020. Retrieved 2020-10-08.