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Mathematical modeling and numerical simulation

Many phenomena occurring in real life applications in natural science, engineering disciplines, as well as the social sciences, and medical science can be represented by mathematical models that describe the essential behavior of a natural or artificial system in order to forecast and control its evolution.  Mathematical modeling and numerical simulations open new perspectives that span science, research and the economy. Using the capabilities of modern numerical methods and supercomputers, increasingly complex problems can be tackled across multiple disciplines.

This knowledge area focuses on numerical simulation and mathematical modeling in scientific computing and computational sciences. Rolf Krause, the knowledge area leader, and his team develop high performance simulation methods for real world applications. They confront the challenge of developing highly efficient solutions by looking beyond the theoretical aspects necessary to derive and understand reliable simulation tools and incorporating their qualitative and quantitative behavior, which can best be understood when employed in the context of complex applications. 

This experiential approach has led to productive collaborations with industry including the recently created Center for Computational Medicine in Cardiology, an interdisciplinary organization that uses large-scale mathematical modeling together with medical image analysis and signal analysis to improve understanding, diagnosis, and treatment of heart failure with cardiac resynchronization therapy.

Link to Knowledge Area:

Center for Computational Medicine in Cardiology

Institute of Computational Science

Knowledge Area Leader: Rolf Krause

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