Skip to main content
Email Print Share

Computational and Data-Enabled Science and Engineering in Mathematical and Statistical Sciences  (CDS&E-MSS)

Name Email Phone Room
Yong  Zeng (703) 292-2301  DMS  
Timothy  Hodges (703) 292-2113  DMS  
Padmanabhan  Seshaiyer (703) 292-2595  DMS  
Christopher  W. Stark (703) 292-4869  DMS  
Vipin  Chaudhary (703) 292-2254  ACI  


Apply to PD 16-8069 as follows:

For full proposals submitted via FastLane: standard NSF Proposal & Award Policies & Procedures Guide proposal preparation guidelines apply.
For full proposals submitted via the NSF Application Guide: A Guide for the Preparation and Submission of NSF Applications via Guidelines applies. (Note: The NSF Application Guide is available on the website and on the NSF website at:

Important Information for Proposers

A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 17-1), is effective for proposals submitted, or due, on or after January 30, 2017. Please be advised that, depending on the specified due date, the guidelines contained in NSF 17-1 may apply to proposals submitted in response to this funding opportunity.


Full Proposal Window

    November 25, 2017 - December 11, 2017

    November 25 - December 9, Annually Thereafter


The CDS&E-MSS program accepts proposals that confront and embrace the
host of mathematical and statistical 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. The goal
of the program is to promote the creation and development of the next
generation of mathematical and statistical theories and tools that will
be essential for addressing such issues. To this end, the program will
support fundamental research in mathematics and statistics whose primary
emphasis will be on meeting the aforementioned computational and
data-related challenges. This program is part of the wider Computational
and Data-enabled Science and Engineering (CDS&E) enterprise in NSF that
seeks to address this emerging discipline; see

The research supported by the CDS&E-MSS program will aim to advance
mathematics or statistics in a significant way and will address
computational or big-data challenges.  Proposals of interest to the
program will include a Principal Investigator or co-Principal
Investigator who is a researcher in the mathematical or statistical
sciences in an area supported by the Division of Mathematical Sciences.
The program encourages submission of proposals that include
multidisciplinary collaborations or the training of mathematicians and
statisticians in CDS&E.


Transdisciplinary Research in Principles of Data Science

Software Infrastructure for Sustained Innovation

Software Development for Cyberinfrastructure

NSF Graduate Research Fellowship Program

Data-Enabled Science in the Mathematical and Physical Sciences

Computational Science

Discovery in Complex or Massive Datasets: Common Statistical Themes

Inventing a New America through Discovery and Innovation in Science, Engineering, and Medicine

MPS Advisory Committee Reports

What Has Been Funded (Recent Awards Made Through This Program, with Abstracts)

Map of Recent Awards Made Through This Program