MathSci.ai is the consulting company of Tammy Kolda and is based in Dublin, California. Dr. Kolda holds a Ph.D. and has over two decades of scientific research experience in mathematical and computational data science, with deep expertise in tensor decompositions for data analysis. She has published extensively, given keynote and plenary lectures at various international conferences, and worked on practical problems in application domains from science, medicine, and business. Her work has been cited over 20,000 times. Her consulting has different flavors, including strategic advice on machine learning research and development that is tailored to the customer’s specific data domain, in-depth technical consulting, development of specialized training courses on tensor decompositions (textbook forthcoming), evaluation of candidates for academic appointments, etc. Inquires about consulting can be sent to the email listed below.
Tamara Kolda is an independent mathematical consultant under the auspices of her company MathSci.ai based in California. From 1999-2021, she was a researcher at Sandia National Laboratories in Livermore, California. She specializes in mathematical algorithms and computation methods for tensor decompositions, tensor eigenvalues, graph algorithms, randomized algorithms, machine learning, network science, numerical optimization, and distributed and parallel computing.
She is currently serving as the founding editor-in-chief for the SIAM Journal on Mathematics of Data Science (SIMODS). She is also a member of the National Academies’ Board on Mathematical Sciences and Analytics (BMSA), the board of advisors for the Institute for Mathematical and Statistical Innovation (IMSI), the SIAM Ethics Committee, the SIAM Block Lecture Selection Committee, the ACM-IEEE CS George Michael Memorial HPC Fellowships Committee, and the Schmidt Postdoctoral Fellowship Selection Committee. She is the founding Chair of the SIAM Activity Group on Equity, Diversity, and Inclusion (SIAG-EDI).
She is a member of the National Academy of Engineering (NAE), Fellow of the Society for Industrial and Applied Mathematics (SIAM), and Fellow of the Association for Computing Machinery (ACM). Other recognitions include two best paper prizes from the IEEE International Conference on Data Mining (ICDM), a best paper prize from the SIAM International Conference on Data Mining (SDM), an R&D100 Award from R&D Magazine, and a Presidential Early Career Award for Scientists and Engineers (PECASE).
Alton S. Householder Postdoc in Scientific Computing, 1997-99
Oak Ridge National Laboratory
PhD in Applied Mathematics, 1997
University of Maryland, College Park (UMCP)
BS in Applied Mathematics, 1992
University of Maryland, Baltimore County (UMBC)
For the past 3+ years, I’ve been chairing an all-star National Academies committee charged with creating a series of posters on Illustrating the Impact of Mathematics. The website is finally live, and I’m really excited to share the results!!
ICERM, Providence, RI, Jan 8, 2024 - Jan 12, 2024 (Organizer)
Oxford, UK, Oct 16, 2023 - Oct 20, 2023
Tokyo, Japan, Aug 20, 2023 - Aug 25, 2023 (Invited Lecturer)
IBM Almaden Research Center, San Jose, CA, Jul 10, 2023 - Jul 21, 2023 (Lecturer)
Evanston, IL, Apr 30, 2023 - May 20, 2023 (Visiting Professor)
Courant Institute, NYU, Apr 21, 2023 (Invited Speaker)
Austin, TX, Apr 3, 2023 - Apr 4, 2023 (Invited Speaker)
Oden Institute, Austin, Texas, Mar 26, 2023 - Apr 8, 2023 (Visiting Scholar)
Oden Institute, Austin, Texas, Jan 29, 2023 - Feb 11, 2023 (Visiting Scholar)