Welcome to SIAM! Applied mathematics, in partnership with computational science, is essential in solving many real-world problems. Our mission is to build cooperation between mathematics and the worlds of science and technology through our publications, research, and community.

New Fellows Announced
The Society for Industrial and Applied Mathematics is pleased to announce the SIAM Fellows Class of 2018. This group includes 28 noteworthy professionals who have made significant contributions to the fields of applied mathematics and computational science. Read more here.

From the Journals

SIAM Journal on Mathematics of Data Science – New!

SIAM newest journal is now taking submissions and will publish work that advances mathematical, statistical, and computational methods in the context of data and information sciences. Authors can submit their work at simods.siam.org. More information on SIMODS is available here.

Gene Golub SIAM Summer School 2018

The 2018 Gene Golub SIAM Summer School will take place June 17-30 at the Double Tree by Hilton in Breckenridge, Colorado, USA. Application deadline is February 1, 2018.
Upcoming Conferences

2018 SIAM Annual Meeting (AN18)

July 9 – 13, 2018 Portland, Oregon, USA -- SIAM’s Annual Meeting provides a broad view of the state of the art in applied mathematics, computational science, and their applications through invited presentations, prize lectures, minitutorials, minisymposia, contributed presentations and posters.

SIAM Presents ... a Featured Lecture from our Archives

Carola-Bibiane Schönlieb, University of Cambridge, United Kingdom, spoke at the 2017 SIAM Annual Meeting on Model-Based Learning in Imaging. In this talk the presenter discusses bilevel optimisation, its analysis and numerical treatment, and show applications to regularization learning, learning of noise models and of sampling patterns in MRI. This talk is available online along with more presentations from this conference and other SIAM meetings at SIAM Presents.
Book of Interest

Numerical Methods for Conservation Laws: From Analysis to Algorithms

Author: Jan S. Hesthaven

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