Q & A with Jack Xin, Multiscale Modeling and Simulation EIC

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. 

I think that multiscale modeling methods and computing skills are essential for all researchers as most exciting and challenging problems contain multiple spatial and temporal scales. MMS is an invaluable resource for learning and keeping one’s toolbox up to date.

You’re in your second year as Editor‐in‐Chief. Prior to your appointment to head up the journal, you were an Associate Editor for eight years. You have some long‐term perspective as a member of the Editorial Board for much of MMS’ history. In what directions do you see the journal heading in the future?

During my eight years as an associate editor, most of the papers I handled for the journal were on first principle based modeling, solving multiscale differential and integral equations of various kinds.  Such work shall continue to be in the majority. A few other directions are on the horizon as well, with several MMS editors personally involved. One is multiscale research based on signal processing and optimization where one works with complex data through filters and sparse representation.  Similar ideas dated back to wavelets and frames, and more recently to compressed sensing in information science. A new trend is data-driven methods where basis functions are learned through multiscale (multi-layer) training (off-line optimization).  Another direction is the development of mathematical tools in information science to yield novel methods for problems in physical, biological and social sciences, or similar interactions among physical, biological and social sciences.

What have you found to be the rewards of being EIC; conversely, what are the challenges, the toughest issues?

I find it rewarding to be EIC, directly observing the evolving research frontier, and promoting excellent mathematical and interdisciplinary work in multiscale modeling.  As EIC, you try to figure out quickly the novelty in each submission or whether it fits MMS, and if so, match it to the expertise of an editor. Sometimes, there is no clear match, or a desired editor is not available.  MMS is one of the SIAM journals with fast average time from submission to acceptance. It is a challenge to keep this number low.  As an interdisciplinary journal, we welcome submissions with novel mathematics from science and engineering communities. There is a lot to do to advertise MMS outside of SIAM and recruit high-quality papers.

What are the most significant of the many recent changes in scholarly publishing? What is the biggest challenge faced by society publishers such as SIAM?

SIAM is a prestigious venue for applied and industrial mathematics publications. There are also many other competitive journals in mathematics and application areas.  A big challenge is to attract more readers and authors to SIAM journals that cover a broad range of fields and topics. Joint society meetings and cross advertisements may help in this effort.

Tell us about your initial interest in applied mathematics. At what point in your life did this become your focus; what drew you to take this path?

My initial interest in applied and computational mathematics came from its fascinating role in airplane design. My father was a professor in aerodynamics and did a lot of wind tunnel experiments in his career. He told me stories of Prandtl, von Karman, and always hoped that mathematics could help him too. Because of his influence, I studied mathematics at Peking University as an undergraduate student.  A few years later, I entered graduate school at Courant Institute where I learned multiscale methods (homogenization) from my advisor Prof. George Papanicolaou, and other faculty there.  At that point, multiscale research and applied mathematics became my focus.  What drew me to take this path was the beauty of homogenization methods, their strong analytical underpinning, interesting computational aspects and wide applicability. Today, homogenization remains a very active research area worldwide and many papers at MMS belong to this category.

MMS is available at epubs.siam.org/journal/MMS. Authors can submit their work for consideration at mms.siam.org.

Jack Xin is Editor in Chief of the SIAM Journal, Multiscale Modeling and Simulation (MMS), and professor of mathematics at University of California, Irvine. 

Mitch Chernoff is the Publications Manager at SIAM.