About IAMCS

UPDATE: The Inaugural KAUST Workshop has been rescheduled for October 6, 2008. Click here for information about the workshop and to register.

Mission

The Institute for Applied Mathematics and Computational Science (IAMCS) is a state-of-the-art, multidisciplinary computational research base with a robust infrastructure that enables large-scale scientific computation research, advanced multidisciplinary learning and education, and a large number of applications in diverse areas of science and engineering of interest to Texas, Saudi Arabia and the world.

Establishment

IAMCS was created in June 2008 under the joint effort of Texas A&M University and its partners, the University of Utah and Rensselaer Polytechnic Institute, in collaboration with King Abdullah University of Science and Technology (KAUST). IAMCS combines the expertise of world renowned researchers and collaborators in mathematics, statistics, and computer science to approach science and engineering issues from different perspectives, thus provides more comprehensive solutions by using flexible model development, predictive assessment, and the ability to handle problems with either excessive or sparse data.

Activities

• Annual research themes structured on three core research areas  

• Research collaborations with KAUST

• Multi-institutional collaborations

• Industry collaboration

• Innovation grants

• Innovative graduate education

• Faculty/student exchanges

• Symposia and workshops
  
  

Education

As part of IAMCS, Texas A&M will launch and maintain graduate and postgraduate fellowships that allow graduate students and postdoctoral researchers to receive supervision, earn degrees, and contribute to research both at U.S. based institutes and at KAUST.

Research Cores

IAMCS’s research and education activities are structured on three core research topics:

1) Forward Multiscale Modeling and Simulation addresses topics related to systematic modeling and simulation approaches for multiscale problems able to make accurate predictions and account for uncertainties due to modeling and measurement errors; 

2) Deterministic and Statistical Methods in Inverse Problems addresses topics where parameters of a “non-transparent” system need to be estimated from external measurements with quantification of associated uncertainties; and

3) Data-Driven Computational Science and Visualization addresses topics related to a data-driven computational science able to dynamically incorporate data into an executing application, and in some cases the ability of the application to dynamically steer the measurement process.
 

Annual Research Themes

Annual applications-related research themes serve as research integrators required for the needed synergy to transform discrete research cores into a unified institute.

• Research Theme, 2008-2009: Computational Earth Sciences

• Research Theme, 2009-2010: Computational Materials Science and Engineering

Subsequent themes will be chosen in conjunction with IAMCS’s External Advisory Board.

Through its research cores and annual themes, IAMCS will ignite creative interactions with its component parts and KAUST, generating new knowledge in critical areas and better preparing the next generation of researchers.

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