SIAM Publications Manager Mitch Chernoff interviews Jack Xin, Multiscale Modeling and Simulation Editor in Chief:
MMS is a relatively young journal, having started publication in 2003. Now publishing to Volume 13, how has the journal progressed?
Thanks to the leadership of my predecessors (Tom Hou and Russel Caflisch), as well as the dedication of the editorial board members over a decade, MMS was in a healthy state with a steady stream of interdisciplinary submissions when I took over in January 2014. Since its launch in 2003, MMS has progressed well and reached the main objective of publishing research articles that focus on the fundamental modeling and computational principles underlying various multiscale methods.
Where do you see it standing out from the competition? Why would you recommend MMS to someone who does not currently have it in their professional focus?
Multiscale modeling and methodologies are fundamental to understanding complex systems and phenomena. These tools are classical for solving problems in physical sciences (e.g., physics and chemistry of fluids, materials, and environment), and continue to evolve due to new challenges and technological advances (e.g., nano sciences). In more recent years, there has been a surge of multiscale methods in information, biological and social sciences. Problems in data analytics and machine learning in computer science also present plenty of opportunities. MMS is thus uniquely positioned to serve the rapidly growing multiscale research community in a broad sense and bridge the gap between mathematics and these application disciplines. (more…)
Chris Johnson (University of Utah) writes:
Recently, the term big data has become ubiquitous. People who can wrangle big data are called data scientists. According to a number of sources, there is a growing need for people trained as data scientists. But what is data science? Is data science its own field or is it an interdisciplinary mix of computer science, mathematics and statistics, and domain knowledge, or perhaps is it really what statisticians have been doing all along? Since data science at scale involves large-scale computation, what is the relation between data science and computational science in research and education?
At the recent SIAM Computational Science and Engineering Conference (CSE 2015), we held what turned out to be a very lively panel to discuss the current and future status of data science, its relationship to computational science, opportunities for data and computational scientists, and educating future data scientists. View a brief video recapping the panel: (more…)
Nick Higham (University of Manchester) writes:
The SIAM Book Committee is currently carrying out a review of the book program. It seeks input from the community about all aspects of the program. Please use the comment box at the end of this post or, alternatively, email me, as the Chair of the Book Committee.
Examples of questions on which input would be valuable include, but are not limited to:
- Are there areas of applied mathematics, or particular topics, in which SIAM is not publishing books but should be?
- What do you think about the quality of SIAM books, both of the content and of the printed book?
- Should SIAM publish more textbooks?
- Is SIAM’s promotion and marketing of books appropriate?
- Is SIAM working with the right model for electronic publishing (currently, the institutional book programme and Google Play for individuals)?
Uli Ruede (University Erlangen-Nuremberg) of the SIAM Activity Group on Computational Science & Engineering (CS&E) writes:
A draft version of our new report on “Future Directions in CSE Education and Research”
has been made accessible on the SIAM CSE Wiki at http://wiki.siam.org/siag-cse. We want to make this white paper representative for the whole CSE community and want to document how our field will impact academia, labs, and industry over the next decades.
This blog provides our medium for discussion and collecting your feedback. We are looking forward to hear what you think of the draft report. Constructive criticism is always welcome and we will try to accommodate your input in the final version of the report, provided that your comments appear here before March 31, 2015.
Please provide feedback using the comments section below.
SIAM Executive Director Jim Crowley writes:
On January 28, I testified before the House Science Committee’s Subcommittee on Energy that oversees the Department of Energy’s Office of Science. The hearing was to review the DOE Office of Science program in Advanced Scientific Computing Research (ASCR), the program that funds advances in high performance computing hardware as well as the basic research programs in applied mathematics and computer science. I was invited to talk about the value of basic research funded by ASCR and challenges for the next wave of high performance computing.
Norman Augustine, formerly CEO of Martin Marietta and now of the Bipartisan Policy Center; Roscoe Giles, of Boston University and Chairman of the DOE Advanced Scientific Computing Advisory Committee; and Dave Turek, Vice President of Technical Computing at IBM also testified at the hearing.
The written testimony, submitted prior to the hearing, was prepared with the help of SIAM’s Committee on Science Policy, chaired by David Levermore, and Lewis-Burke Associates, a firm who assists our Science Policy Committee.
Read the full testimony:
James Crowley Written Testimony for House SST January 28 2015
SIAM President Pamela Cook and Past President Irene Fonseca write:
Many of you have shared your concerns that NSF will be sunsetting funding for the Institute for Math and its Applications (IMA) and the Math Biology Institute (MBI, potentially to be continued through joint funding with the Biological Sciences Directorate). As current and immediate past presidents of SIAM, we share your concern. The Division of Mathematical Sciences has faced a difficult budget period and made decisions on these institutes after a thorough review process. Other institutes under review, including MSRI, IPAM, and ICERM – appear to have been recommended for renewal. NSF cannot share additional information until the review process has been completed, but we hope that NSF will eventually provide information on their vision for the institutes and clear policies concerning their longevity and metrics for success. We also recognize the strong role IMA and MBI play in anchoring applied mathematics in the mid-west and connecting the community to industry, and hope that NSF will think thoughtfully about how to maintain these functions even as funding for these institutes is ended. We look forward to hearing from NSF regarding future support of the applied math community in light of these divestments.
Please feel free to share your thoughts and feedback through the comments section below.
The Editors of SIAM Review recap the SIGEST paper in the September 2014 issue of SIREV:
The SIGEST paper in this issue, “The Diameter of the Rubik’s Cube Group Is Twenty,” by Tomas Rokicki, Herbert Kociemba, Morley Davidson, and John Dethridge, is from the SIAM Journal on Discrete Mathematics.
The year 2014 marked the 40th birthday of the Rubik’s cube puzzle. I expect that most readers know what Rubik’s cube is, and direct the few of you who do not to
where you’ll get a far better account of the story than any printed page will ever give you. (more…)
Des Higham, Section Editor of SIAM Review gives an overview of the Survey and Review paper in the latest issue:
In this issue, Survey and Review readers are invited to “Meet the Flockers.” The article “Heterophilious Dynamics Enhances Consensus,” by Sebastien Motsch and Eitan Tadmor, considers models of flocking and opinion formation as prototypes for self-organized dynamics. The model classes surveyed are nonlinear ODE systems where each “agent” or “particle” in the system is summarized by a vector of state values that may represent geographical location, velocity, or some other time-dependent attribute such as an opinion. The rates of change of each agent’s coordinates are then assumed to be driven by that agent’s relative difference with each other agent; see equation (1.1). The key property of interest in this article is the emergence over long time intervals of a single cluster, or consensus, where all agents tend to a common state, as happens when a jury reaches a unanimous verdict or a collection of birds forms a single flock.
The authors distinguish between models with global and local connectivity, depending upon whether influence is felt between all agents or just those who are sufficiently close in coordinate space, respectively. The techniques of analysis used to establish the results include energy and spectral methods, and they involve concepts from graph theory to handle the time-dependent connectivity structure defined by the interactions. As indicated by the choice of title, the work emphasizes the counterintuitive phenomenon that, in appropriate circumstances, notably with local models, propensity for consensus is enhanced through heterophily—a preference for bonding more closely with far-neighbors than with near-neighbors in coordinate space. In this sense, it is birds of a very different feather that stick together. (more…)
Lou Rossi, Section Editor of SIAM Review gives an overview of the Education paper in the latest issue:
One of the great ironies in mathematics instruction is that typical instructional activities are bound to textbooks. Students expect mathematical structures, concepts, and techniques to begin and end in their texts when, in fact, they spend most of their days surrounded by great mathematical problems. In the fall, students learn about vector fields in calculus, but are never asked to give a thought to the leaves swirling outside the classroom window. The mathematical sciences are the sciences of abstraction, but observations of the world around us can inspire us to think about mathematical objects and problems in new and exciting ways. In this issue of SIAM Review, our Education section features two articles, the first of which is a perfect example of finding interesting mathematical problems in sports. In this case, the sport is rugby and asking a very simple question about the best approach to earning extra points reveals a very elaborate answer. The problem evolves into an expression that needs to be solved numerically, giving us a nice segue into our second paper, which explores fixed point iterations and Newton’s methods for solving nonlinear problems; so by coincidence our two Education papers follow a natural sequence. (more…)
Evelyn Sander, Section Editor of SIAM Review, recaps the Research Spotlights paper in the September 2014 issue of SIREV:
Accurately estimating solutions for models of physical systems with steep internal layers is an important but difficult numerical problem. For example, the formation of alloys—such as the creation of stainless steel—involves phase separation at the atomic level of its metallic components. This can be successfully modeled, but the delicate sharp interface structure makes computational methods for approximating solutions an ambitious problem. Sharp interface systems arise in the form of elliptic partial differential equations in an array of fluids problems, in semiconductor device simulations, and in microstructure evolution of materials. (more…)