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Interdisciplinary Research in Hazards and Disasters  (Hazards SEES)  Crosscutting Programs

CONTACTS

Name Dir/Div Name Dir/Div
Gregory  J. Anderson GEO/EAR  Leah  Nichols SBE/BCS 
Amanda (Manda)  S. Adams GEO/AGS  Donna  Blackman GEO/OCE 
Stephen  Meacham OD/IIA  Kishor  Mehta ENG/CMMI 
Anita  Nikolich CISE/ACI  Robert  E. O'Connor SBE/SES 
Junping  Wang MPS/DMS  Dennis  E. Wenger ENG/CMMI 

PROGRAM GUIDELINES

Solicitation  14-581

DUE DATES

Full Proposal Deadline Date:  December 3, 2014

SYNOPSIS

Hazards SEES is a program involving multiple NSF Directorates and Offices (CISE, ENG, GEO, MPS, OIIA, and SBE) that seeks to: (1) advance understanding of the fundamental processes associated with specific natural hazards and technological hazards linked to natural phenomena, and their interactions; (2) better understand the causes, interdependences, impacts, and cumulative effects of these hazards on individuals, the natural and built environment, and society as a whole; and (3) improve capabilities for forecasting or predicting hazards, mitigating their effects, and enhancing the capacity to respond to and recover from resultant disasters.  The overarching goal of Hazards SEES is to catalyze well-integrated interdisciplinary research efforts in hazards-related science and engineering in order to reduce the impact of hazards, enhance the safety of society, and contribute to sustainability.

Hazards SEES seeks research projects that will productively cross the boundaries of the atmospheric and geospace, earth, and ocean sciences; computer and information science (including cyberinfrastructure); engineering; mathematics and statistics; and social, economic, and behavioral sciences.  Successful proposals will integrate across multiple disciplines to promote research that advances new paradigms that contribute to creating a society resilient to hazards. Hazards SEES intends to transform hazards and disaster research by fostering the development of interdisciplinary research that allows for appropriately targeted data collection, integration, and management; modeling (including predictive models for real-time decision making); visualization and simulation; data analytics and data-driven discovery; real-time sensing; cross-cutting knowledge development; and synthesis of applicable models and theory.  Proposals must demonstrate the inclusion of the appropriate expertise to address the research questions, hypotheses, and problems being posed. 

RELATED URLS

Frequently Asked Questions (FAQs) for Hazards SEES 2014/2015 Competition

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

Map of Recent Awards Made Through This Program



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