Math at the Interface with Computer Sciences at NSF

December 15, 2006

NSF has issued a new solicitation in Mathematical Sciences (NSF/DMS) under the mathematical sciences priority area dealing with the interface of research in the mathematical sciences related to several specific areas in computer science. The details of the solicitation may be found at

A short synmpopsis from NSF follows.


Dear Colleagues,

An updated program solicitation is now available:

Mathematical Sciences: Innovations at the Interface with Computer Sciences (MSPA-MCS)

Please see NSF 07-534

Full Proposal Deadline Date: March 12, 2007


This solicitation describes the opportunities available for support through the NSF Mathematical Sciences Priority Area in the category of Interactions between Mathematical Sciences and Computer Sciences (MSPA-MCS).

Investments in the MSPA-MCS program aim to deepen support of collaborative research involving fundamental mathematics and statistics together with computer science. The primary focus is on the areas of mathematical and statistical challenges posed by large data sets, managing and modeling uncertainty, and modeling complex nonlinear systems.

In FY 2007, the Division of Mathematical Sciences (DMS) of the Directorate for Mathematical and Physical Sciences and the Division of Computing and Communication Foundations (CCF) of the Directorate for Computer and Information Science plan to support research and development teams focusing on mathematical and computational innovations relevant to areas of specific interest:

* Statistical learning in nonlinear spaces, transductive learning; models inspired by statistical physics; game theoretic ideas as applied to learning theory.

* Algorithms, techniques, and theories for the modeling, reduction, and visualization of large, real-time data sets.

As this joint funding will focus on areas of mutual interest, proposals must originate from teams involving collaborators of mathematical scientists and computer scientists. Proposals should offer new approaches and promise significant breakthroughs in these areas, developing rigorous mathematical/statistical and computational foundations to advance understanding in both the mathematical sciences and computer science.

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