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By Pranay Seshadri, Shaowu Yuchi, and Geoffrey T. ParksSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 4, Page 1301-1322, January 2019. Ridge functions have recently emerged as a powerful set of ideas for subspace-based dimension reduction. In...
By Leslie Greengard and Shidong JiangSIAM Review, Volume 61, Issue 4, Page 733-755, January 2019. We present a new integral representation for the unsteady, incompressible Stokes or Navier--Stokes equations, based on a linear combination...
By Jon Cockayne, Chris J. Oates, T. J. Sullivan, and Mark GirolamiSIAM Review, Volume 61, Issue 4, Page 756-789, January 2019. Over forty years ago average-case error was proposed in the applied mathematics literature as an alternative criterion with which...
By Gábor PatakiSIAM Review, Volume 61, Issue 4, Page 839-859, January 2019. Semidefinite programs (SDPs)---some of the most useful and versatile optimization problems of the last few decades---are often...
By Catherine F. Higham and Desmond J. HighamSIAM Review, Volume 61, Issue 4, Page 860-891, January 2019. Multilayered artificial neural networks are becoming a pervasive tool in a host of application fields. At the heart of...
By Guo Luo and Thomas Y. HouSIAM Review, Volume 61, Issue 4, Page 793-835, January 2019. Whether the three-dimensional incompressible Euler equations can develop a singularity in finite time from smooth initial data is one...
By Olga Y. KushelSIAM Review, Volume 61, Issue 4, Page 643-729, January 2019. Multiplicative and additive $D$-stability, diagonal stability, Schur $D$-stability, and $H$-stability are classical concepts which arise in studying linear dynamical...
By Darinka DentchevaSIAM Review, Volume 61, Issue 4, Page 837-838, January 2019. The Education section of SIAM Review presents two papers in this issue. In the first paper Gábor Pataki ...
By Misha E. KilmerSIAM Review, Volume 61, Issue 4, Page 731-731, January 2019. Numerical solution of the Navier--Stokes equations in both two and three dimensions is the subject of the first of...
By Volker H. SchulzSIAM Review, Volume 61, Issue 4, Page 895-906, January 2019. The book reviews section serves to inform readers about current important books from a personal point of view. However,...
By The EditorsSIAM Review, Volume 61, Issue 4, Page 791-791, January 2019. The SIGEST article in this issue is “Formation of Finite-Time Singularities in the 3D Axisymmetric Euler Equations: A Numerics...
By J. M. Sanz-SernaSIAM Review, Volume 61, Issue 4, Page 641-641, January 2019. It is a safe bet that most readers use matrices in their work. It is often of interest to...
By Kookjin Lee, Howard C. Elman, and Bedřich SousedíkSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 4, Page 1275-1300, January 2019. We study an iterative low-rank approximation method for the solution of the steady-state stochastic Navier--Stokes equations...
Have you ever tried to explain why applied math matters to your non-specialist friends and colleagues? How does it impact their everyday life? How is it shaping the future of technology? SIAM has ...
By Ru Zhang, C. Devon Lin, and Pritam RanjanSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 4, Page 1245-1274, January 2019. Computer simulators are widely used to describe and explore complex physical processes. The simulator outputs...
By Joseph L. Hart and Pierre A. GremaudSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 4, Page 1224-1244, January 2019. Global sensitivity analysis (GSA) quantifies the influence of uncertain variables in a mathematical model. The Sobol'...
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By M. Gunzburger, T. Iliescu, M. Mohebujjaman, and M. SchneierSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 4, Page 1162-1184, January 2019. In this paper, we propose a filter-based stabilization of reduced order models (ROMs) for uncertainty quantification...
By Bamdad HosseiniSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 4, Page 1185-1223, January 2019. We introduce two classes of Metropolis--Hastings algorithms for sampling target measures that are absolutely continuous...
By Matthias H. Y. TanSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 4, Page 1133-1161, January 2019. Partial differential equation (PDE) models are often solved numerically. The solution to a PDE model,...
By Arvind K. Saibaba, Johnathan Bardsley, D. Andrew Brown, and Alen AlexanderianSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 1105-1131, January 2019. Hierarchical models in Bayesian inverse problems are characterized by an assumed prior probability distribution for the...
By Mohammad MotamedSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 1076-1104, January 2019. We introduce and study a new class of partial differential equations (PDEs) with hybrid fuzzy-stochastic parameters,...
By Giovanni Rabitti and Emanuele BorgonovoSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 1060-1075, January 2019. The recent work of Owen [SIAM/ASA J. Uncertainty Quantification, 2 (2014), pp. 245--251] has introduced the...
By Giovanni Dematteis, Tobias Grafke, and Eric Vanden-EijndenSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 1029-1059, January 2019. A central problem in uncertainty quantification is how to characterize the impact that our incomplete knowledge...
By Jie Shen, Jie Xu, and Jiang YangSIAM Review, Volume 61, Issue 3, Page 474-506, January 2019. We propose a new numerical technique to deal with nonlinear terms in gradient flows. By introducing...
By Arjun S. Ramani, Nicole Eikmeier, and David F. GleichSIAM Review, Volume 61, Issue 3, Page 549-595, January 2019. Common models for random graphs, such as Erdös--Rényi and Kronecker graphs, correspond to generating random adjacency matrices where each...
By Johan S. H. van Leeuwaarden, Britt W. J. Mathijsen, and Bert ZwartSIAM Review, Volume 61, Issue 3, Page 403-440, January 2019. Multiserver queueing systems describe situations in which users require service from multiple parallel servers. Examples include check-in lines...
By Ben Adcock and Daan HuybrechsSIAM Review, Volume 61, Issue 3, Page 443-473, January 2019. Functions of one or more variables are usually approximated with a basis: a complete, linearly independent system of functions...
By T. J. Dodwell, C. Ketelsen, R. Scheichl, and A. L. TeckentrupSIAM Review, Volume 61, Issue 3, Page 509-545, January 2019. In this paper we address the problem of the prohibitively large computational cost of existing Markov chain Monte Carlo...
By Roger Cropp and John NorburySIAM Review, Volume 61, Issue 3, Page 596-622, January 2019. Obligate mutualist interactions appear to be ubiquitous in nature but cannot be described by the simple models that have...
By The EditorsSIAM Review, Volume 61, Issue 3, Page 507-507, January 2019. In this section we present “Multilevel Markov Chain Monte Carlo,” by T. J. Dodwell, C. Ketelsen, R. Scheichl, and...
By Volker H. SchulzSIAM Review, Volume 61, Issue 3, Page 625-640, January 2019. This time, the Book Reviews section has a large portion of books devoted to system dynamics and applications. The...
By Misha E. KilmerSIAM Review, Volume 61, Issue 3, Page 441-441, January 2019. The issue of accurate function approximation is an important topic in numerical analysis. The first Research Spotlights article,...
By J. M. Sanz-SernaSIAM Review, Volume 61, Issue 3, Page 401-401, January 2019. Johan S. H. van Leeuwaarden, Britt W. J. Mathijsen, and Bert Zwart are the authors of the Survey and...
By Darinka DentchevaSIAM Review, Volume 61, Issue 3, Page 547-548, January 2019. This issue of SIAM Review presents two papers in the Education section. The first is “Coin-Flipping, Ball-Dropping, and Grass-Hopping...
By Agnimitra Dasgupta and Debraj GhoshSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 1007-1028, January 2019. Estimation of failure probabilities is computationally expensive, and the usage of reduced order models (ROM) holds...
By David Swigon, Shelby R. Stanhope, Sven Zenker, and Jonathan E. RubinSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 975-1006, January 2019. Random parameter models are used to describe natural phenomena governed by deterministic processes in situations where...
By U. Khristenko, L. Scarabosio, P. Swierczynski, E. Ullmann, and B. WohlmuthSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 948-974, January 2019. We consider the generation of samples of a mean-zero Gaussian random field with Matérn covariance function....
By Lukas Herrmann, Christoph Schwab, and Jakob ZechSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 913-947, January 2019. In bounded, polygonal domains $D \subset \Bbb{R}^d$, we analyze solution regularity and sparsity for computational uncertainty...
By Matthew J. Zahr, Kevin T. Carlberg, and Drew P. KouriSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 877-912, January 2019. This work introduces a new method to efficiently solve optimization problems constrained by partial differential equations...
By Ian Vernon, Samuel E. Jackson, and Jonathan A. CummingSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 838-876, January 2019. Computer models are now widely used across a range of scientific disciplines to describe various complex...
By James M. Scott, M. Paul Laiu, and Cory D. HauckSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 806-837, January 2019. We show the convergence of the zero relaxation limit of $2 \times 2$ systems of hyperbolic...
By Christopher Müller, Sebastian Ullmann, and Jens LangSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 3, Page 787-805, January 2019. We study the iterative solution of linear systems of equations arising from stochastic Galerkin finite element...
By Nathalie Ayi and Erwan FaouSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 760-785, January 2019. We present an asymptotic preserving scheme based on a micro-macro decomposition for stochastic linear transport equations...
By Furong Sun, Robert B. Gramacy, Benjamin Haaland, Earl Lawrence, and Andrew WalkerSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 720-759, January 2019. Obtaining accurate estimates of satellite drag coefficients in low Earth orbit is a crucial component in...
By David AristoffSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 685-719, January 2019. We study parallel replica dynamics in a general setting. We introduce a trajectory fragment framework...
By Christian Clason, Tapio Helin, Remo Kretschmann, and Petteri PiiroinenSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 652-684, January 2019. Uncertainty quantification requires efficient summarization of high- or even infinite-dimensional (i.e., nonparametric) distributions based on, e.g.,...
By Roland Pulch and Florian AugustinSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 634-651, January 2019. In uncertainty quantification, critical parameters of mathematical models are substituted by random variables. We consider dynamical...
By Dave Osthus, Scott A. Vander Wiel, Nelson M. Hoffman, and Frederick J. WysockiSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 604-633, January 2019. Scientists often predict physical outcomes, e.g., experimental results, with the assistance of computer codes that, at...
By Benjamin PeherstorferSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 579-603, January 2019. Multifidelity Monte Carlo (MFMC) estimation combines low- and high-fidelity models to speed up the estimation of...
By Dan Wilson and Bard ErmentroutSIAM Review, Volume 61, Issue 2, Page 277-315, January 2019. While phase reduction is a tremendously useful tool for understanding the dynamics of weakly perturbed limit cycle oscillators,...
By Bernhard Beckermann and Alex TownsendSIAM Review, Volume 61, Issue 2, Page 319-344, January 2019. Matrices with displacement structure, such as Pick, Vandermonde, and Hankel matrices, appear in a diverse range of applications. In...
By Samuel Awoniyi and Ira WheatonSIAM Review, Volume 61, Issue 2, Page 347-360, January 2019. This education article presents a case for first courses on Markov chain modeling to include the topic “sojourn time...
By Guodong Shi, Claudio Altafini, and John S. BarasSIAM Review, Volume 61, Issue 2, Page 229-257, January 2019. A signed network is a network in which each link is associated with a positive or negative sign....
By Richard D. NeidingerSIAM Review, Volume 61, Issue 2, Page 361-381, January 2019. Techniques of univariate Newton interpolating polynomials are extended to multivariate data points by different generalizations and practical algorithms. ...
By Beate Ehrhardt and Patrick J. WolfeSIAM Review, Volume 61, Issue 2, Page 261-276, January 2019. We characterize the large-sample properties of network modularity in the presence of covariates, under a natural and flexible null...
By Rui TuoSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 553-578, January 2019. Identification of model parameters in computer simulations is an important topic in computer experiments. We propose...
By Misha E. KilmerSIAM Review, Volume 61, Issue 2, Page 259-259, January 2019. The paper “Network Modularity in the Presence of Covariates," by Beate Ehrhardt and Patrick J. Wolfe, is the first...
By Darinka DentchevaSIAM Review, Volume 61, Issue 2, Page 345-346, January 2019. This issue of SIAM Review contains two papers in the Education section. The first paper is “Case for First...
By J. M. Sanz-SernaSIAM Review, Volume 61, Issue 2, Page 227-227, January 2019. ``Dynamics over Signed Networks,” by Guodong Shi, Claudio Altafini, and John S. Baras, is the Survey and Review article...
By Volker H. SchulzSIAM Review, Volume 61, Issue 2, Page 385-400, January 2019. Sometimes, people confuse artificial neural networks (ANNs) with real biological brains, at least metaphorically. The section starts with a...
By The EditorsSIAM Review, Volume 61, Issue 2, Page 317-317, January 2019. The SIGEST article in this issue is “Bounds on the Singular Values of Matrices with Displacement Structure,” by Bernhard...
By Christian Kahle, Kei Fong Lam, Jonas Latz, and Elisabeth UllmannSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 526-552, January 2019. We consider the inverse problem of parameter estimation in a diffuse interface model for tumor growth....
By Michael B. Giles and Abdul-Lateef Haji-AliSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 497-525, January 2019. We investigate the problem of computing a nested expectation of the form $\mathbb{P} {[\mathbb{E}[{X | Y]}...
By Rodrigo Iza-Teran and Jochen GarckeSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 472-496, January 2019. We propose a new data analysis approach for the efficient postprocessing of bundles of finite element...
By Colin Cotter, Simon Cotter, and Paul RussellSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 444-471, January 2019. Markov chain Monte Carlo methods are a powerful and commonly used family of numerical methods for...
By Adrien Spagnol, Rodolphe Le Riche, and Sébastien Da VeigaSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 417-443, January 2019. The optimization of high dimensional functions is a key issue in engineering problems but it frequently...
By Andreas AdelmannSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 2, Page 383-416, January 2019. Using a cyclotron-based model problem, we demonstrate for the first time the applicability and usefulness of...
By N. Nüsken and G. A. PavliotisSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 324-382, January 2019. In this paper we develop a general framework for constructing and analyzing coupled Markov chain Monte...
By Constantin Grigo and Phaedon-Stelios KoutsourelakisSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 292-323, January 2019. Well-established methods for the solution of stochastic partial ...
By Sergey Dolgov and Robert ScheichlSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 260-291, January 2019. We consider the approximate solution of parametric PDEs using the low-rank tensor train (TT) decomposition. Such...
By Daniel J. Perry, Robert M. Kirby, Akil Narayan, and Ross T. WhitakerSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 203-231, January 2019. We propose a novel approach to allocating resources for expensive simulations of high fidelity models when...
By Zachary del Rosario, Minyong Lee, and Gianluca IaccarinoSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 232-259, January 2019. Lurking variables represent hidden information and preclude a full understanding of phenomena of interest. Detection is...
By Martin J. Gander and Hui ZhangSIAM Review, Volume 61, Issue 1, Page 3-76, January 2019. Solving time-harmonic wave propagation problems by iterative methods is a difficult task, and over the last two decades an...
By Eddie Nijholt, Bob Rink, and Jan SandersSIAM Review, Volume 61, Issue 1, Page 121-155, January 2019. Many systems in science and technology are networks: they consist of nodes with connections between them. Examples include electronic...
By Gjerrit MeinsmaSIAM Review, Volume 61, Issue 1, Page 159-184, January 2019. A complete theory of dimensional and scaling analysis is presented and its power is demonstrated through a series of...
By Simone Carlo Surace, Anna Kutschireiter, and Jean-Pascal PfisterSIAM Review, Volume 61, Issue 1, Page 79-91, January 2019. Particle filters are a popular and flexible class of numerical algorithms to solve a large class of nonlinear filtering...
By Peter G. Fennell and James P. GleesonSIAM Review, Volume 61, Issue 1, Page 92-118, January 2019. Multistate dynamical processes on networks, where nodes can occupy one of a multitude of discrete states, are gaining widespread...
By Silviu Filip, Aurya Javeed, and Lloyd N. TrefethenSIAM Review, Volume 61, Issue 1, Page 185-205, January 2019. The usual way in which mathematicians work with randomness is by a rigorous formulation of the idea of Brownian...
By Darinka DentchevaSIAM Review, Volume 61, Issue 1, Page 157-158, January 2019. In this issue, the Education section of SIAM Review presents two papers. The first is “Dimensional and Scaling Analysis,”...
By Misha E. KilmerSIAM Review, Volume 61, Issue 1, Page 77-77, January 2019. Short and to the point, “How to Avoid the Curse of Dimensionality: Scalability of Particle Filters with and...
By Volker H. SchulzSIAM Review, Volume 61, Issue 1, Page 209-225, January 2019. This time, the Book Reviews section has a large portion of reviews on books devoted to applications---in particular medical...
By J. M. Sanz-SernaSIAM Review, Volume 61, Issue 1, Page 1-1, January 2019. The Survey and Review article in this issue is “A Class of Iterative Solvers for the Helmholtz Equation: Factorizations,...
By The EditorsSIAM Review, Volume 61, Issue 1, Page 119-119, January 2019. Over the last fifteen years, SIAM Review has published a range of articles in the general area of network...
By Andreas Van Barel and Stefan VandewalleSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 174-202, January 2019. This paper addresses optimization problems constrained by partial differential equations with uncertain coefficients. In particular, the...
By Kayla D. Coleman, Allison Lewis, Ralph C. Smith, Brian Williams, Max Morris, and Bassam KhuwailehSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 117-142, January 2019. Recent developments in the field of reduced-order modeling---and, in particular, active subspace construction---have made it possible...
By Toshihiro Yamada and Kenta YamamotoSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 143-173, January 2019. This paper shows a higher order discretization scheme for the Bismut--Elworthy--Li formula, the differentiation of diffusion...
By Gianluca Detommaso, Tim Dodwell, and Rob ScheichlSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 93-116, January 2019. In this paper, we present a generalization of the multilevel Monte Carlo (MLMC) method to a...
By Joseph L. Hart, Julie Bessac, and Emil M. ConstantinescuSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 67-92, January 2019. Global sensitivity analysis (GSA) is frequently used to analyze the influence of uncertain parameters in mathematical...
By Minyong R. LeeSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 53-66, January 2019. The active subspace is useful in reducing the dimensionality of the input space of a function....
By Wanting Xu, Michael L. Stein, and Ian WisherSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 31-52, January 2019. Analyzing chaotic observations generated from some unknown nonlinear dynamics presents significant challenges for modeling the process...
By Frédéric Cérou, Bernard Delyon, Arnaud Guyader, and Mathias RoussetSIAM/ASA Journal on Uncertainty Quantification, Volume 7, Issue 1, Page 1-30, January 2019. Adaptive multilevel splitting (AMS) is a generic Monte Carlo method for Markov processes that simulates rare...
Uncertainty quantification (UQ) is essential for providing informative computational predictions in many branches of science and engineering. It is an interdisciplinary field built on a broad range ...
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.
SIAM awards the prize with the Association for Computing Machinery (ACM) for outstanding contributions to the development and use of mathematical and computational tools and methods for the solution of science and engineering problems.
Established in 1979 in honor of James H. Wilkinson, the prize is awarded to an individual in their early career for recent contributions to numerical analysis and scientific computing.
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.
The prize recognizes innovative software in scientific computing by researchers in the earlier stages of their career. Starting in 2019, SIAM will award the prize every four years at the SIAM Conference on Computational Science and Engineering.
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.
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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.
Established in 2016, the prize is awarded to an individual in their early career for research contributions in the field of uncertainly quantification.
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 Prizes bring attention to papers published in SIAM journals. Three awards are 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.
Looking for financial support to further your research? Fellowships often provide funding plus experiential learning opportunities to young researchers. Learn more about fellowship opportunities.
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Internships allow you to network and forge connections for future job possibilities, while also exploring possible areas of interest. Look at this list of companies who offer valuable opportunities.
Our community is founded on igniting groundbreaking developments in applied math and computational science. Take a deeper dive into your area of study with one of these opportunities.