Tammy Kolda is an independent consultant in mathematical data science with 24 years of experience applying tensor decomposition, randomized algorithms, and high-performance computing to scientific and industrial problems. A member of the National Academy of Engineering and a Fellow of both SIAM and ACM, she blends deep algorithmic design with practical scientific software development and a track record of impactful R&D at Sandia and Oak Ridge National Laboratories. Currently advising via MathSci.ai and serving as a Distinguished Visiting Professor at Northwestern, she focuses on efficient, scalable methods and serves on advisory and evaluation boards. Her work is notable for translating advanced numerical linear algebra into production-ready tools that accelerate real-world data science workflows.
24 years of coding experience
22 years of employment as a software developer
UMBC
Ph.D., Applied Mathematics, Ph.D., Applied Mathematics at University of Maryland
L-BFGS-B, converted from Fortran to C, with Matlab wrapper
Contributions:1 push, 1 branch in 1 year 6 months
fortran-package-managermatlabfortranabaqusbfgs
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