SCIENTIFIC COMPUTING AND IMAGING INSTITUTE
at the University of Utah

An internationally recognized leader in visualization, scientific computing, and image analysis

Numerical simulation of real-world phenomena provides fertile ground for building interdisciplinary relationships. The SCI Institute has a long tradition of building these relationships in a win-win fashion – a win for the theoretical and algorithmic development of numerical modeling and simulation techniques and a win for the discipline-specific science of interest. High-order and adaptive methods, uncertainty quantification, complexity analysis, and parallelization are just some of the topics being investigated by SCI faculty. These areas of computing are being applied to a wide variety of engineering applications ranging from fluid mechanics and solid mechanics to bioelectricity.

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- Parallel Computing
- GPUs
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- Finite Element Methods
- Uncertainty Quantification
- GPUs
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- Approximation theory and methods
- Sparse and regularized representations
- Mathematical shape analysis
- High-order numerical methods
- Data assimilation
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- Data science
- Deep learning
- Stochastic optimization
- Large scale scientific computing