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TITLE: Dear Colleague Letter:Computational and Data-Enabled Science and
Engineering in Mathematical and Statistical Sciences (CDS&E-MSS)
DATE: 11/22/2012
NSF 12-018
Dear Colleague Letter: Computational and Data-Enabled Science and
Engineering in Mathematical and Statistical Sciences (CDS&E-MSS)
Dear Colleagues:
The conduct of scientific research is being revolutionized by
developments in the availability of computational resources and
digital datasets. The last three decades have seen advances of roughly
nine orders of magnitude in computing capability, together with deep
advances in computational algorithms. These advances allow
computational and multiscale simulations of unprecedented scope and
accuracy. Simultaneous advances in digital data collection technology
are proceeding at an even faster pace, with the result that enormous
datasets are now generated routinely by scientific experiments and
observations of natural phenomena. The result is a scientific
revolution in the scope, use, and production of data.
As did digital computation itself, such data-intensive science is
driving revolutionary advances in mathematics and statistics. How are
features, let alone new laws of nature, to be found in the vast
volumes of data being generated and collected? How can disparate data,
from simulations and observations, different instruments and multiple
communities, be combined to advance knowledge?
The Division of Mathematical Sciences and the Office of
Cyberinfrastructure of the National Science Foundation recognize the
importance of fundamental mathematical and statistical research in
this field of computational and data-enabled science and engineering
(CDS&E) and envision that the mathematical and statistical research
communities will play a leading role in the future development of this
emerging science. In partnership with the Office of
Cyberinfrastructure, the CDS&E-MSS program in DMS supports fundamental
mathematical and statistical research at the core of this emerging
discipline. The goal of the program is to promote the creation,
development, and application of the next generation of mathematical
and statistical theories and tools that will be essential for
addressing the challenges presented to the scientific and engineering
communities by the ever-expanding role of computational modeling and
simulation on the one hand, and the explosion in production of digital
and observational data on the other. To this end, the program will
support fundamental research in mathematics and statistics, including
transition to practice, whose primary emphasis will be on meeting the
aforementioned computational and data-related challenges. The program
has strong interest in multidisciplinary collaboration and the
training of next-generation mathematicians and statisticians firmly
grounded in CDS&E.
Examples in which mathematical and statistical research enables
advances in CDS&E include, but are not limited to:
* Sophisticated computational/statistical modeling for simulation,
prediction, and assessment in computation-intensive and
data-intensive scientific problems.
* State-of-the-art tools and theory in statistical inference and
statistical learning for knowledge discovery from massive,
complex, and dynamic data sets.
* General theory and algorithms for advancing large-scale modeling
of problems that present particular computational difficulties,
such as strong heterogeneities and anisotropies, multi-physics
coupling, multiscale behavior, stochastic forcing, uncertain
parameters or dynamic data, and long-time behavior.
* Study of mathematical, statistical, and stochastic properties of
networks.
* Mathematical and statistical challenges of uncertainty
quantification.
* Development of numerical, symbolic, and statistical theory and
tools to uncover and study analytical, topological, algebraic,
geometric, and number-theoretic structures relevant for
large-scale data acquisition, data security, and cybersecurity.
Subject to availability of funds and quality of proposals, up to $5M
will be made available for this program in fiscal year 2012. For the
full program description, see
[1]http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504687&org=DMS&from
=home
Sastry Pantula
Director, Division of Mathematical Sciences
References
1. http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504687&org=DMS&from=home