SIAM Celebrates Mathematics and Statistics Awareness Month 2025

Each year, the Joint Policy Board for Mathematics—a collaboration between SIAM, the American Mathematical Society, the American Statistical Association, and the Mathematical Association of America—holds a month-long celebration for Mathematics and Statistics Awareness Month to enhance public understanding and appreciation of mathematics and statistics.

Mathematical and statistical research drives technological innovation and leads to discoveries of broad societal importance across many scientific fields. Throughout the month of April, universities, high schools, student groups, research institutions, public information offices, and other related organizations host math-related workshops, competitions, lectures, and other activities. We encourage you to join the celebration and share your math-related festivities using the hashtag #MathStatMonth on social media.

To mark Mathematics and Statistics Awareness Month, SIAM is highlighting members of our community, featuring Dr. Orly Alter and Dr. Katarzyna Świrydowicz.

Orly Alter

Dr. Orly Alter earned her Ph.D. in applied physics from Stanford University (1999), where her work contributed to gravitational wave detection and quantum computing. During her postdoctoral fellowship at Stanford’s School of Medicine, she invented the pioneering concept of the "eigengene," a key innovation in genomic data analysis, earning recognition as one of the top 50 most cited Proceedings of the National Academy of Sciences papers of all time. She later joined the University of Texas at Austin, where she developed mathematical and computational physics approaches for analyzing large-scale biological data, before moving to Utah. She is currently a Utah Science, Technology, and Research (USTAR) Associate Professor of Bioengineering and Human Genetics at the Scientific Computing and Imaging (SCI) Institute and Huntsman Cancer Institute, University of Utah. She is also the Chief Scientific Officer and co-founder of Prism AI Therapeutics, Inc. and serves as a scientific advisory board member for the NCI-DOE Cancer Moonshot collaboration.

Dr. Alter’s research focuses on developing quantum mechanics-based multi-tensor AI/ML methods to identify clinically actionable, mechanistically interpretable predictors from high-dimensional multi-omic data. Her work has been supported with grants by the National Science Foundation, the National Institutes of Health, and the Department of Energy. Among her many honors, she was a 2014 American Association of Physicists in Medicine Science Council Session Winner Lecture awardee, a 2005 International Linear Algebra Society Linear Algebra and Its Application Lecturer, and a finalist for the 1998 American Physical Society Outstanding Doctoral Thesis Research in Atomic, Molecular, or Optical Physics Award. Learn more about Dr. Alter.

Dr. Alter has been a member of SIAM for 22 years, attending, presenting, and chairing multi-session minisymposia at several SIAM conferences including the 2018 SIAM Conference on Applied Linear Algebra. Recently, she served as an organizing committee member and panel moderator of the 2025 SIAM Conference on Computational Science and Engineering.

Watch the video below to learn more about Dr. Alter’s career and her advice to early career professionals.

Katarzyna (Kasia) Świrydowicz 

Dr. Kasia Świrydowicz works at AMD as a Senior Member of Technical Staff. She received her Ph.D. in mathematics from Virginia Tech (2017), after which she completed a short postdoc at Virginia Tech before moving to a second postdoctoral opportunity in the National Renewable Energy Laboratory. She was then hired as a staff scientist in the Pacific Northwest National Laboratory, where she worked for three years before starting her current position at AMD in 2024.

Dr. Świrydowicz’s research revolves around linear solvers – the algorithms used to solve very large, sparse systems of equations – and their efficient implementation, squeezing out every last bit of performance from modern hardware. What has been a driving force in her research is a question of efficiency: how to design algorithms in such a way that they naturally benefit from parallelism, and how to implement them in ways that optimize hardware use without sacrificing stability or other mathematical properties. Throughout her career, Dr. Świrydowicz has worked on Krylov subspace recycling, low-synchronization linear solvers, randomized linear solvers, refactorization, and the influence of algorithmic choices on power consumption. She is currently working on a project involving use of mixed precision in scientific workloads, among other things.  

Dr. Świrydowicz’s involvement with SIAM began as a graduate student with the SIAM Student Chapter at Virginia Tech. Coming from Europe, she wasn’t initially familiar with SIAM, but through student-led seminars, she connected with peers who shared her passion for applied mathematics. The first large conference she attended and presented at was the 2014 SIAM Annual Meeting in Chicago, Illinois. She was pleasantly surprised by the friendly atmosphere and the number of connections she made by simply talking to other participants. Through SIAM conferences, Dr. Świrydowicz has had the opportunity to present her work to a welcoming and engaged audience, receive feedback, find new collaborators, and strengthen existing connections. Over the last six years as a SIAM member, she has regularly attended the SIAM Conferences on Computational Science and Engineering, among others, and currently serves as a member of the SIAM Industry Committee. As Dr. Świrydowicz works from home, her involvement in SIAM allows her to stay connected with the broader scientific community through various SIAM communications, online events, activity groups, and conferences.

To early career professionals, Dr. Świrydowicz advises others to take any advice given cautiously. “People often have good intentions, but it does not necessarily mean they know what is best for you– only you can know this,” she said.