About MathSci.ai
In the realm of AI, how can you differentiate the hype from the
technologies that can truly benefit your organization?
MathSci.ai provides unbiased, objective advice to clients in the following areas:
- Identifying opportunities in which AI will advance your mission
- Understanding the mathematical and statistical underpinnings of AI technologies
- Developing appropriate data resources for AI training and evaluation
- Navigating ethical considerations and protecting confidential data
- Interacting with AI technology vendors and in-house data scientists
- Setting realistic expectations and timelines for AI adoption
With a distinguished career, including over 20 years at Sandia National
Laboratories and over 5 years in consulting,
Tamara Kolda has worked with
prominent nonprofits, government agencies, contractors, and
technology companies.
Based in the San Francisco Bay Area, she offers flexible, hourly-based assistance
online or in person.
Inquires about consulting can be sent to tammy.kolda@mathsci.ai.
Bio
Tamara Kolda, Ph.D., is an independent mathematical consultant under
the auspices of her company MathSci.ai based in California and founded
in 2021.
From 1999-2021, she was a Distinguished Member of the
Technical Staff at Sandia National Laboratories in Livermore,
California.
She is a
member of the U.S. National Academy of Engineering (NAE), Fellow of
the Society for Industrial and Applied Mathematics (SIAM), and Fellow
of the Association for Computing Machinery (ACM).
Her research is in the broad domain of mathematical data science.
She has authored 75+ journal articles, conference proceedings papers,
and book chapters.
She is the author of two books:
Tensor Decompositions for Data Science
and
Unlocking LaTeX Graphics: A Concise Guide to TikZ/PGF and PGFPLOTS.
She is the SIAM Vice President for Publications, co-chair of the 2027 SIAM Conference on Linear Algebra (LA27), and
Program Chair of the SIAM Activity Group on Equity,
Diversity, and Inclusion (SIAG-EDI).
She also sits on the board of the First Proof Foundation, which is dedicated to understanding the capabilities of AI systems on problems that come up in math research.
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