Mathematical modeling of complex problems is actually a network of activities involving interdisciplinary teams collaborating closely with specialists in modeling methods and tools. Over the years, many of the activities within IIASA and its collaborating institutions have required nonstandard methods and tools for model specification, generation, and analysis, which resulted in the collaboration of our staff with various teams at different stages of the modeling process, and development of: novel modeling paradigms for adequate representation of complex problems, effective treatment of uncertainty and risk, methods and tools for model support of the whole modeling cycle, including analysis and the management of huge amounts of data, and development of specialized algorithms for solving various types of computational problems.

In the coming years, research of the IME Project will be composed of the following four mutually linked activities:

• Structured Modeling Technology (SMT)
• Coping with Endogenous Uncertainty and Risk
• Integrated Model Analysis
• Water: Scarcity and Floods
• GHGs: robust solutions

The demand for advanced modeling support will increase with: the growing complexity of IIASA's models, the needs of integrating models and/or data developed by different programs, the demand for effective treatment of uncertainty, and the need for transparency and documentation of modeling activities. Thus we plan to continue providing advanced modeling support with new methods and tools that will be built on the legacy developed during past successful cooperation with several of IIASA's programs.

For further information please see the IME Project's Research Plan and the proposal for the IME Project extension, both accepted by the IIASA Council, in 2005 and 2008, respectively.

The IME Project officially began on January 1, 2006. Previously, it carried out its research as the Advanced Modeling Project as part of the Risk, Modeling and Society Program.

Responsible for this page: Suchitra Subramanian
Last updated: 17 Nov 2011