This research area covers mathematics and computational methods in data science that includes machine learning and data mining, intertwined with other key areas such as statistics, computer science, network science, and signal processing - all within the context of data science as well as applications of mathematical methods in data/information processing to science and engineering problems.

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Data Science Book Series

Did you know – SIAM recently launched a new Data Science Book Series! Data science is a forward-looking field and is seeing tremendous energy and growth. Have book ideas? We want to hear about them.

By Manuchehr Aminian
The work of Michael Jordan’s (University of California, Berkeley) research group was a highlight of the 2020 SIAM Conference on Mathematics of Data Science (MDS20), ...

By Brianna C. Heggeseth and Chad M. Topaz
In 2017, social media discussions about the opening of a new wing at the Massachusetts Museum of Contemporary Art first alerted us to the dearth of ...

By Yiming Sun, Yang Guo, Charlene Luo, Joel Tropp, and Madeleine Udell SIAM Journal on Mathematics of Data Science, Volume 2, Issue 4, Page 1123-1150, January 2020. This paper describes a new algorithm for computing a low-Tucker-rank approximation of a tensor....

By Yiming Sun, Yang Guo, Charlene Luo, Joel Tropp, and Madeleine Udell SIAM Journal on Mathematics of Data Science, Volume 2, Issue 4, Page 1123-1150, January 2020. This paper describes a new algorithm for computing a low-Tucker-rank approximation of a tensor....

By Elena Bossolini, Morten Brøns, and Kristian Uldall Kristiansen SIAM Review, Volume 62, Issue 4, Page 869-897, January 2020. In mechanics, one often describes microscopic processes such as those leading to friction between relative interfaces using macroscopic variables...

By Giacomo Nannicini SIAM Review, Volume 62, Issue 4, Page 936-981, January 2020. This paper is a gentle but rigorous introduction to quantum computing intended for discrete mathematicians. Starting from a small...

By Caleb Ju and Edgar Solomonik SIAM Review, Volume 62, Issue 4, Page 743-777, January 2020. The prevalence of convolution in applications within signal processing, deep neural networks, and numerical solvers has motivated the development...

By Alexandria Volkening, Daniel F. Linder, Mason A. Porter, and Grzegorz A. Rempala SIAM Review, Volume 62, Issue 4, Page 837-865, January 2020. Forecasting elections---a challenging, high-stakes problem---is the subject of much uncertainty, subjectivity, and media scrutiny. To shed light on this...

By Sanjeeva Balasuriya SIAM Review, Volume 62, Issue 4, Page 781-816, January 2020. Uncertainties in velocity data are often ignored when computing Lagrangian particle trajectories of fluids. Modeling these as noise...

By Yuanzhao Zhang and Adilson E. Motter SIAM Review, Volume 62, Issue 4, Page 817-836, January 2020. The field of network synchronization has seen tremendous growth following the introduction of the master stability function (MSF) formalism,...

By Xiaocheng Shang and Martin Kröger SIAM Review, Volume 62, Issue 4, Page 901-935, January 2020. We study the time correlation functions of coupled linear Langevin dynamics with and without inertial effects, both analytically and...

By Chunfeng Cui, Kaiqi Zhang, Talgat Daulbaev, Julia Gusak, Ivan Oseledets, and Zheng Zhang SIAM Journal on Mathematics of Data Science, Volume 2, Issue 4, Page 1096-1122, January 2020. Active subspace is a model reduction method widely used in the uncertainty quantification community....

By Darinka Dentcheva SIAM Review, Volume 62, Issue 4, Page 899-900, January 2020. This issue of SIAM Review presents two papers in the Education section. The first paper, “Time Correlation Functions of...

By Misha E. Kilmer SIAM Review, Volume 62, Issue 4, Page 779-780, January 2020. We are fortunate to have three topically diverse papers featured in Research Spotlights in the current issue. The...

By Volker H. Schulz SIAM Review, Volume 62, Issue 4, Page 985-994, January 2020. The first and featured review is on the book Introduction to Numerical Methods for Variational Problems, by Hans...

By J. M. Sanz-Serna SIAM Review, Volume 62, Issue 4, Page 741-741, January 2020. Finding the convolution of two vectors is a ubiquitous task in applied mathematics. Signal processing, image processing, deep neural...

By The Editors SIAM Review, Volume 62, Issue 4, Page 867-867, January 2020. In this section we present “A Stiction Oscillator with Canards: On Piecewise Smooth Nonuniqueness and Its Resolution by Regularizing...

By Tamara G. Kolda and David Hong SIAM Journal on Mathematics of Data Science, Volume 2, Issue 4, Page 1066-1095, January 2020. Tensor decomposition is a well-known tool for multiway data analysis. This work proposes using...

By Roman Vershynin SIAM Journal on Mathematics of Data Science, Volume 2, Issue 4, Page 1004-1033, January 2020. Overwhelming theoretical and empirical evidence shows that mildly overparametrized neural networks---those with more connections...

By Philip S. Chodrow SIAM Journal on Mathematics of Data Science, Volume 2, Issue 4, Page 1034-1065, January 2020. We study the expected adjacency matrix of a uniformly random multigraph with fixed degree...

By Abhishek Gupta, Hao Chen, Jianzong Pi, and Gaurav Tendolkar SIAM Journal on Mathematics of Data Science, Volume 2, Issue 4, Page 967-1003, January 2020. Recursive stochastic algorithms have gained significant attention in the recent past due to data-driven...

By Talal Ahmed, Haroon Raja, and Waheed U. Bajwa SIAM Journal on Mathematics of Data Science, Volume 2, Issue 4, Page 944-966, January 2020. This paper studies a tensor-structured linear regression model with a scalar response variable and...

By Miles E. Lopes, Suofei Wu, and Thomas C. M. Lee SIAM Journal on Mathematics of Data Science, Volume 2, Issue 4, Page 921-943, January 2020. When randomized ensemble methods such as bagging and random forests are implemented, a basic...

By Christa Cuchiero, Martin Larsson, and Josef Teichmann SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 901-919, January 2020. A recent paradigm views deep neural networks as discretizations of certain controlled ordinary differential...

By William H. Weir, Benjamin Walker, Lenka Zdeborová, and Peter J. Mucha SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 872-900, January 2020. Modularity-based community detection encompasses a number of widely used, efficient heuristics for identification of...

By Thomas Y. Hou, Zhenzhen Li, and Ziyun Zhang SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 840-871, January 2020. In this paper, we provide some analysis on the asymptotic escape of strict saddles...

By Tamir Bendory and Dan Edidin SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 809-839, January 2020. Motivated by the X-ray crystallography technology to determine the atomic structure of biological...

By Charles Fefferman, Sergei Ivanov, Matti Lassas, and Hariharan Narayanan SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 770-808, January 2020. We consider the reconstruction of a manifold (or, invariant manifold learning), where...

By Nicolas García Trillos and Ryan W. Murray SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 705-739, January 2020. This paper investigates the use of methods from partial differential equations and the calculus...

By Dario Fasino and Francesco Tudisco SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 740-769, January 2020. The use of higher-order stochastic processes such as nonlinear Markov chains or vertex-reinforced random...

By Paul Breiding and Orlando Marigliano SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 683-704, January 2020. Consider the set of solutions to a system of polynomial equations in many variables....

By Patrick De Leenheer SIAM Review, Volume 62, Issue 3, Page 716-726, January 2020. We present an elementary proof of a generalization of Kirchhoff's matrix tree theorem to directed, weighted graphs. The proof...

By Mahesh Chandra Mukkamala, Peter Ochs, Thomas Pock, and Shoham Sabach SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 658-682, January 2020. Backtracking line-search is an old yet powerful strategy for finding better step sizes to...

By Lek-Heng Lim SIAM Review, Volume 62, Issue 3, Page 685-715, January 2020. This is an elementary introduction to the Hodge Laplacian on a graph, a higher-order generalization of the graph Laplacian....

By Andrii Mironchenko and Christophe Prieur SIAM Review, Volume 62, Issue 3, Page 529-614, January 2020. In a pedagogical but exhaustive manner, this survey reviews the main results on input-to-state stability (ISS) for infinite-dimensional systems....

By Ernesto Estrada, Gissell Estrada-Rodriguez, and Heiko Gimperlein SIAM Review, Volume 62, Issue 3, Page 617-645, January 2020. In a complex system, the interplay between the internal structure of its entities and their interconnection may play a...

By Jed A. Duersch and Ming Gu SIAM Review, Volume 62, Issue 3, Page 661-682, January 2020. Rank-revealing matrix decompositions provide an essential tool in spectral analysis of matrices, including the Singular Value Decomposition (SVD) and...

By Vicky Chuqiao Yang, Daniel M. Abrams, Georgia Kernell, and Adilson E. Motter SIAM Review, Volume 62, Issue 3, Page 646-657, January 2020. Since the 1960s, Democrats and Republicans in the U.S. Congress have taken increasingly polarized positions, while the public's policy...

By Darinka Dentcheva SIAM Review, Volume 62, Issue 3, Page 683-683, January 2020. This issue of SIAM Review contains two papers in the Education section. The first paper, “Hodge Laplacians on Graphs,”...

By Misha E. Kilmer SIAM Review, Volume 62, Issue 3, Page 615-615, January 2020. In this issue, Research Spotlights features two exciting and topically diverse articles. The authors of the first article...

By J. M. Sanz-Serna SIAM Review, Volume 62, Issue 3, Page 527-527, January 2020. Andrii Mirochenko and Christophe Prieur are the authors of “Input-to-State Stability of Infinite-Dimensional Systems: Recent Results and Open Questions,”...

By Volker H. Schulz SIAM Review, Volume 62, Issue 3, Page 729-739, January 2020. These are difficult times, but some circumstances make the work in our Book Reviews section even more difficult. Due...

By The Editors SIAM Review, Volume 62, Issue 3, Page 659-659, January 2020. The SIGEST article in this issue, “Randomized Projection for Rank-Revealing Matrix Factorizations and Low-Rank Approximations,” by Jed A. Duersch...

By Julius Berner, Philipp Grohs, and Arnulf Jentzen SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 631-657, January 2020. The development of new classification and regression algorithms based on empirical risk minimization (ERM)...

By Ben Adcock and Juan M. Cardenas SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 607-630, January 2020. In this paper, we address the problem of approximating a multivariate function defined on...

By Ilja Klebanov, Ingmar Schuster, and T. J. Sullivan SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 583-606, January 2020. Conditional mean embeddings (CMEs) have proven themselves to be a powerful tool in many...

By Bao Wang, Binjie Yuan, Zuoqiang Shi, and Stanley J. Osher SIAM Journal on Mathematics of Data Science, Volume 2, Issue 3, Page 559-582, January 2020. Empirical adversarial risk minimization is a widely used mathematical framework to robustly train...

By Patrick L. Combettes and Jean-Christophe Pesquet SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 529-557, January 2020. Obtaining sharp Lipschitz constants for feed-forward neural networks is essential to assess their robustness...

By Yuan Li, Benjamin Mark, Garvesh Raskutti, Rebecca Willett, Hyebin Song, and David Neiman SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 480-504, January 2020. Sparse models for high-dimensional linear regression and machine learning have received substantial attention over...

By Thomas Reeves, Anil Damle, and Austin R. Benson SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 505-528, January 2020. Given a set of snapshots from a temporal network we develop, analyze, and experimentally...

By Anru R. Zhang, Yuetian Luo, Garvesh Raskutti, and Ming Yuan SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 444-479, January 2020. In this paper, we develop a novel procedure for low-rank tensor regression, namely Importance...

By Marcel Klatt, Carla Tameling, and Axel Munk SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 419-443, January 2020. We derive limit distributions for various empirical regularized optimal transport quantities between probability...

By Zixuan Cang and Guo-Wei Wei SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 396-418, January 2020. Persistent homology is a powerful tool for characterizing the topology of a data set...

By Ling Guo, Akil Narayan, and Tao Zhou SIAM Review, Volume 62, Issue 2, Page 483-508, January 2020. Polynomial approximations constructed using a least-squares approach form a ubiquitous technique in numerical computation. One of the simplest ways...

By Lloyd N. Trefethen SIAM Review, Volume 62, Issue 2, Page 439-462, January 2020. Boundary-value problems involving the linear differential equation $\varepsilon y'' - x y' + y = 0$ have surprising properties...

By Yair Carmon and John C. Duchi SIAM Review, Volume 62, Issue 2, Page 395-436, January 2020. We consider minimization of indefinite quadratics with either trust-region (norm) constraints or cubic regularization. Despite the nonconvexity of these...

By Anne Greenbaum, Ren-Cang Li, and Michael L. Overton SIAM Review, Volume 62, Issue 2, Page 463-482, January 2020. We present first-order perturbation analysis of a simple eigenvalue and the corresponding right and left eigenvectors of a general...

By Philipp Grohs, Sarah Koppensteiner, and Martin Rathmair SIAM Review, Volume 62, Issue 2, Page 301-350, January 2020. The problem of phase retrieval, i.e., the problem of recovering a function from the magnitudes of its Fourier...

By Michael T. Schaub, Austin R. Benson, Paul Horn, Gabor Lippner, and Ali Jadbabaie SIAM Review, Volume 62, Issue 2, Page 353-391, January 2020. Using graphs to model pairwise relationships between entities is a ubiquitous framework for studying complex systems and data. Simplicial...

By Volker H. Schulz SIAM Review, Volume 62, Issue 2, Page 511-526, January 2020. I am writing these lines in April 2020 while science is in lockdown mode globally. They will be published...

By The Editors SIAM Review, Volume 62, Issue 2, Page 393-393, January 2020. The SIGEST article in this issue, “First-Order Methods for Nonconvex Quadratic Minimization,” by Yair Carmon and John C. Duchi,...

By Misha E. Kilmer SIAM Review, Volume 62, Issue 2, Page 351-351, January 2020. The current issue of SIAM Review features the Research Spotlights article “Random Walks on Simplicial Complexes and the Normalized...

By Darinka Dentcheva SIAM Review, Volume 62, Issue 2, Page 437-438, January 2020. The Education section of SIAM Review presents three papers in this issue. In the first paper Lloyd N. Trefethen...

By J. M. Sanz-Serna SIAM Review, Volume 62, Issue 2, Page 299-299, January 2020. In a previous issue of SIAM Review, I started my introduction to the Survey and Review section by saying...

By Ming-Jun Lai and Daniel Mckenzie SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 368-395, January 2020. We show how one can phrase the cut improvement problem for graphs as a...

By Michael T. Schaub, Santiago Segarra, and John N. Tsitsiklis SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 335-367, January 2020. We consider a blind identification problem in which we aim to recover a statistical...

By Charles Clum, Dustin G. Mixon, and Theresa Scarnati SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 309-334, January 2020. We introduce a new Procrustes-type method called matching component analysis to isolate components in...

By Xinye Zheng, Jianbo Ye, James Z. Wang, and Jia Li SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 284-308, January 2020. Optimal transport (OT) is a prominent framework for point set registration, that is, to...

By Yuan Zhang, Elizaveta Levina, and Ji Zhu SIAM Journal on Mathematics of Data Science, Volume 2, Issue 2, Page 265-283, January 2020. Community detection has been well studied in network analysis, but the more realistic case...

By Nguyen Hieu Thao, David Russell Luke, Oleg Soloviev, and Michel Verhaegen SIAM Journal on Mathematics of Data Science, Volume 2, Issue 1, Page 246-263, January 2020. In this paper, we propose and investigate the phase retrieval problem with the a...

By Han-Wen Kuo, Yuqian Zhang, Yenson Lau, and John Wright SIAM Journal on Mathematics of Data Science, Volume 2, Issue 1, Page 216-245, January 2020. We study the short-and-sparse (SaS) deconvolution problem of recovering a short signal $\boldsymbol{a}_0$ and...

By Rachel Minster, Arvind K. Saibaba, and Misha E. Kilmer SIAM Journal on Mathematics of Data Science, Volume 2, Issue 1, Page 189-215, January 2020. Many applications in data science and scientific computing involve large-scale datasets that are expensive...

By Alireza Aghasi, Afshin Abdi, and Justin Romberg SIAM Journal on Mathematics of Data Science, Volume 2, Issue 1, Page 158-188, January 2020. We develop a fast, tractable technique called Net-Trim for simplifying a trained neural network....

By Emmanuel Abbe, Enric Boix-Adserà, Peter Ralli, and Colin Sandon SIAM Journal on Mathematics of Data Science, Volume 2, Issue 1, Page 132-157, January 2020. Spectral algorithms, such as principal component analysis and spectral clustering, rely on the extremal...

By Eric Mazumdar, Lillian J. Ratliff, and S. Shankar Sastry SIAM Journal on Mathematics of Data Science, Volume 2, Issue 1, Page 103-131, January 2020. We introduce a general framework for competitive gradient-based learning that encompasses a wide breadth...

By Volker H. Schulz SIAM Review, Volume 62, Issue 1, Page 283-297, January 2020. The frame for the Book Reviews section this time is formed by the books of two very well known...

By The Editors SIAM Review, Volume 62, Issue 1, Page 197-197, January 2020. The SIGEST article in this issue, “Asymptotically Compatible Schemes for Robust Discretization of Parametrized Problems with Applications to Nonlocal...

By Misha E. Kilmer SIAM Review, Volume 62, Issue 1, Page 131-131, January 2020. Tensors, or multiway arrays, are often used for storage of high-dimensional data. In order to have compression, completion,...

By J. M. Sanz-Serna SIAM Review, Volume 62, Issue 1, Page 1-1, January 2020. Bernard Brogliato and Aneel Tanwani are the authors of “Dynamical Systems Coupled with Monotone Set-Valued Operators: Formalisms, Applications, Well-Posedness,...

By Darinka Dentcheva SIAM Review, Volume 62, Issue 1, Page 229-230, January 2020. The Education section of SIAM Review presents three papers in this issue. In the first paper Robert M. Corless...

By Xiaochuan Tian and Qiang Du SIAM Review, Volume 62, Issue 1, Page 199-227, January 2020. Many problems in nature, being characterized by a parameter, are of interest both with a fixed parameter value...

By Bernard Brogliato and Aneel Tanwani SIAM Review, Volume 62, Issue 1, Page 3-129, January 2020. This survey article addresses the class of continuous-time systems where a system modeled by ordinary differential equations is...

By David Hong, Tamara G. Kolda, and Jed A. Duersch SIAM Review, Volume 62, Issue 1, Page 133-163, January 2020. Tensor decomposition is a fundamental unsupervised machine learning method in data science, with applications including network analysis and sensor...

By Tracy L. Stepien, Eric J. Kostelich, and Yang Kuang SIAM Review, Volume 62, Issue 1, Page 244-263, January 2020. Most undergraduates have limited experience with mathematical modeling. In an effort to respond to various initiatives, such as the...

By Antônio Francisco Neto SIAM Review, Volume 62, Issue 1, Page 264-280, January 2020. In this work we introduce a new operator based approach to matrix analysis. Our main technical tool comprises an...

By Nawaf Bou-Rabee and Miranda C. Holmes-Cerfon SIAM Review, Volume 62, Issue 1, Page 164-195, January 2020. Sticky Brownian motion is the simplest example of a diffusion process that can spend finite time both in the...

By Robert M. Corless and Leili Rafiee Sevyeri SIAM Review, Volume 62, Issue 1, Page 231-243, January 2020. We look at two classical examples in the theory of numerical analysis, namely, the Runge example for interpolation and...

By Vasileios Maroulas, Farzana Nasrin, and Christopher Oballe SIAM Journal on Mathematics of Data Science, Volume 2, Issue 1, Page 48-74, January 2020. Persistence diagrams offer a way to summarize topological and geometric properties latent in datasets....

By Raphaël Berthier, Francis Bach, and Pierre Gaillard SIAM Journal on Mathematics of Data Science, Volume 2, Issue 1, Page 24-47, January 2020. Consider a network of agents connected by communication links, where each agent holds a...

By Stefanie Günther, Lars Ruthotto, Jacob B. Schroder, Eric C. Cyr, and Nicolas R. Gauger SIAM Journal on Mathematics of Data Science, Volume 2, Issue 1, Page 1-23, January 2020. Residual neural networks (ResNets) are a promising class of deep neural networks that have...

By Holger Drees, Anja Janßen , Sidney I. Resnick, and Tiandong Wang SIAM Journal on Mathematics of Data Science, Volume 2, Issue 1, Page 75-102, January 2020. Power-law distributions have been widely observed in different areas of scientific research. Practical estimation...

By Manuchehr Aminian
The work of Michael Jordan’s (University of California, Berkeley) research group was a highlight of the 2020 SIAM Conference on Mathematics of Data Science (MDS20), ...

By Brianna C. Heggeseth and Chad M. Topaz
In 2017, social media discussions about the opening of a new wing at the Massachusetts Museum of Contemporary Art first alerted us to the dearth of ...

By James Case
Smart Baseball: The Story Behind the Old Stats That Are Ruining the Game, the New Ones That Are Running It, And the Right Way to Think About Baseball. By Keith Law. William ...

By Aparna Chandramowlishwaran
Deep learning (DL)—a specific approach to artificial intelligence (AI) that is based on artificial neural networks—is now recognized as one of the biggest ...

By Manuchehr Aminian
In recent years, deep learning (DL) has inspired a myriad of advances within the scientific computing community. This subset of artificial intelligence relies on multiple ...

The SIAM Student Paper Prize is awarded annually to the student author(s) of the most outstanding paper(s) accepted by SIAM journals within the three years preceding the nomination deadline. Starting with the 2018 award, the focus of the prize is to recognize outstanding scholarship by students in SIAM journals.

The Pioneer Prize is awarded every four years at the International Council for Industrial and Applied Mathematics (ICIAM) Congress to one individual for pioneering work introducing applied mathematical methods and scientific computing techniques to an industrial problem area or a new scientific field of applications. Nominations can be submitted via the ICIAM website.

This joint prize was established in 2002 to honor Sonia Kovalevsky and her work on the theory of differential equations. It is awarded to anyone in the scientific or engineering community whose work highlights the achievements of women in applied and computational mathematics. Nominations can be submitted via the AWM website.

This prize was created in 2013 to emphasize George Pólya’s legacy of communicating mathematics effectively. It joins two long-standing Pólya prizes SIAM has awarded in combinatorics and other fields beginning in 1969.

Through the generosity and inspiration of Gerald and Judith Porter, the Mathematical Association of America (MAA), American Mathematical Society (AMS), and SIAM offer this annual lecture at the Joint Mathematics Meetings. The lecture, first awarded in 2010, is given on a mathematical topic accessible to the broader community.

Named in honor of I. E. Block, a co-founder and the first managing director of SIAM, this lecture is open to the public at the SIAM Annual Meeting. It is intended to encourage public appreciation of applied mathematics and computational science by reaching out to the local community.

Established in 1959, the prize honors John von Neumann, a founder of modern computing. The prize is awarded annually for distinguished contributions to applied mathematics and for the effective communication of these ideas to the community.

The JPBM Communications Award is given annually to reward and encourage communicators who, on a sustained basis, bring mathematical ideas and information to non-mathematical audiences. The prize may be awarded in two categories: For Public Outreach and For Expository and Popular Books. Nominations can be submitted via the AMS website.

The prize was established in 1986 in memory of Richard C. DiPrima, who served SIAM for many years and in 1979–1980 as SIAM President. It aims to recognize an early career researcher in applied mathematics and is based on the doctoral dissertation.

The prize recognizes students for outstanding solutions to real world math problems. It is awarded to two of the teams judged "Outstanding" in the Mathematical Contest in Modeling (MCM) administered annually by the Consortium for Mathematics and Its Applications (COMAP). Registration is accepted via the COMAP website.

The SIAM Outstanding Paper Prize is not currently active. For the 20 years before it was discontinued in 2019, the SIAM Outstanding Paper Prizes brought attention to papers published in SIAM journals. Three awards were made each year to the authors of papers deemed by SIAM journal editors-in-chief worthy of particular attention.

The prize, established in 1985 and originally intended to be awarded periodically, is now awarded annually for contributions to the advancement of applied mathematics on the national or international level.

The purpose of this activity group is to advance the mathematics of data science, to highlight the importance and benefits of data science, and to identify and explore the connections between data science and other applied sciences.

SIAM Journal on Mathematics of Data Science (SIMODS) publishes work that advances mathematical, statistical, and computational methods in the context of data and information sciences. We invite papers that present significant advances in this context, including applications to science, engineering, business, and medicine.

Multiscale Modeling & Simulation
SIAM J. on Applied Algebra and Geometry
SIAM J. on Applied Dynamical Systems
SIAM J. on Applied Mathematics
SIAM J. on Computing
SIAM J. on Control and Optimization
SIAM J. on Discrete Mathematics
SIAM J. on Financial Mathematics
SIAM J. on Imaging Sciences
SIAM J. on Mathematical Analysis
SIAM J. on Matrix Analysis and Applications
SIAM J. on Numerical Analysis
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SIAM J. on Scientific Computing
SIAM/ASA J. on Uncertainty Quantification
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Theory of Probability & Its Applications

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