Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

Scientific Computing

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.


Martin Berzins

Parallel Computing

Mike Kirby

Finite Element Methods
Uncertainty Quantification

Valerio Pascucci

Scientific Data Management

Chris Johnson

Problem Solving Environments

Amir Arzani

Scientific machine learning
Data-driven fluid flow modeling

Funded Research Projects:

Publications in Scientific Computing:

Applications in Computational Medicine using SCIRun: A Computational Steering Programming Environment
C.R. Johnson, S.G. Parker. In Supercomputer `95, Edited by H.W. Meuer, Springer-Verlag, pp. 2--19. 1995.

Applications of Automatic Mesh Generation and Adaptive Methods in Computational Medicine
J.A. Schmidt, C.R. Johnson, J.C. Eason, R.S. MacLeod. In Modeling, Mesh Generation, and AdaptiveMethodsforPartial Differential Equations, Edited by I. Babuska and J.E. Flaherty and W.D. Henshaw and J.E. Hopcroft and J.E. Oliger and T. Tezduyar, Springer-Verlag, pp. 367--390. 1995.

Direct and Inverse Bioelectric Field Problems
C.R. Johnson. In Computational Science Education Project, Edited by E. Oliver and M. Strayer and V. Meiser and D. Zachmann and R. Giles, DOE, Washington, D.C. 1995.

SCIRun: A Scientific Programming Environment for Computational Steering
S.G. Parker, C.R. Johnson. In Proceedings of the 1995 ACM/IEEE Conference on Supercomputing, San Diego, California, USA, Supercomputing '95, No. 52, ACM, New York, NY, USA 1995.
ISBN: 0-89791-816-9
DOI: 10.1145/224170.224354

Numerical Methods for Bioelectric Field Problems
C.R. Johnson. In The Biomedical Engineering Handbook, Edited by J.D. Bronzino, CRC Press, Boca Ratan pp. 161--188. 1995.

Defibsim: An Interactive Defibrillation Device Design Tool
J.A. Schmidt, C.R. Johnson. In IEEE Engineering in Medicine and Biology Society 17th Annual International Conference, IEEE Press, pp. 305--306. 1995.

Dynamic Load-Balancing For PDE Solvers On Adaptive Unstructured Meshes
C. Walshaw, M. Berzins. In Concurrency, Vol. 7, No. 1, pp. 17--28. 1995.

The Effects of Inhomogeneities and Anisotropies on Electrocardiographic Fields: A Three-Dimensional Finite Element Study
R.N. Klepfer, C.R. Johnson, R.S. MacLeod. In IEEE Engineering in Medicine and Biology Society 17th Annual International Conference, IEEE Press, pp. 233--234. 1995.

A Physically Based Mesh Generation Algorithm: Applications in Computational Medicine
D.M. Weinstein, S.G. Parker, C.R. Johnson. In IEEE Engineering in Medicine and Biology Society 16th Annual International Conference, IEEE Press, pp. 718--719. 1994.

A Computational Steering Model Applied to Problems in Medicine
C.R. Johnson, S.G. Parker. In Supercomputing 94, IEEE Press, pp. 540--549. 1994.

A Morphing Algorithm for Generating Near Optimal Grids: Applications in Computational Medicine
School of Computing Technical Report, S.G. Parker, D.M. Weinstein, C.R. Johnson. No. UUCS-94-014, University of Utah, 1994.

Computational Engineering and Science at the University of Utah
C.R. Johnson, P. Alfeld. In IEEE Computational Science and Engineering, pp. 7--9. 1994.

An Automatic Adaptive Refinement and Derefinement Method
F. Yu, C.R. Johnson. In Proceedings of the 14th IMACS World Congress, pp. 1555--1557. 1994.

High Performance Computing in Medicine: Direct and Inverse Problems in Cardiology
C.R. Johnson, R.S. MacLeod. In IEEE Engineering in Medicine and Biology Society 15th Annual International Conference, pp. 582--583. 1993.

A 3D Cellular Automata Model of the Heart
P.B. Gharpure, C.R. Johnson. In IEEE Engineering in Medicine and Biology Society 15th Annual International Conference, IEEE Press, pp. 752--753. 1993.

Computer Simulations Reveal Complexity of Electrical Activity in the Human Thorax
C.R. Johnson, R.S. MacLeod, M.A. Matheson. In Computers in Physics, Vol. 6, pp. 230--237. May/June, 1992.

An Adaptive Theta Method for the Solution of Stiff and Non-stiff Differential Equations
M. Berzins, R.M. Furzeland. In Applied Numerical Mathematics, Vol. 9, pp. 1--19. 1992.

Berzins, M. and R.M. Furzeland, An adaptive theta method for the solution of stiff and nonstiff differential
equations, Applied Numerical Mathematics 9 (1992) 1-19.

This paper describes a new adaptive method that has been developed to give improved efficiency for solving
differential equations where the degree of stiffness varies during the course df the integration or is not known
beforehand. The method is a modification of the theta method, in which the new adaptive strategy is to
automatically select the value of theta and to switch between functional iteration and Newton iteration for the
solution of the nonlinear equations arising at each integration step. The criteria for selecting theta and for
switching are established by optimising the permissible step size.

The performance of the adaptive methods is demonstrated on a range of test problems including one arising
from the method of lines solution of a convectixr-dominated partial differential equation. In some cases the new
approach halves the amount of computational work.

Effects of Anistropy and Inhomogeneity on Electrocardiographic Fields: A Finite Element Study
C.R. Johnson, R.S. MacLeod, A. Dutson. In Engineering in Medicine and Biology Society 14th Annual International Conference, IEEE Press, pp. 2009--2010. 1992.

A Computer Model for the Study of Electrical Current Flow in the Human Thorax
C.R. Johnson, R.S. MacLeod, P.R. Ershler. In Computers in Biology and Medicine, Vol. 22, No. 5, Elsevier BV, pp. 305--323. 1992.

Electrocardiography has played an important role in the detection and characterization of heart function, both in normal and abnormal states. In this paper we present an inhomogeneous, anisotropic computer model of the human thorax for use in electrocardiography with emphasis on the calculation of transthoracic potential and current distributions. Knowledge of the current pathways in the thorax has many applications in electrocardiography and has direct utility in studies pertaining to cardiac defibrillation, forward and inverse problems, impedance tomography, and electrode placement in electrocardiography.

Keywords: scalar field methods, vector field methods, tensor field methods, cardiac heart, scientific visualization

Computational Studies of Forward and Inverse Problems in Electrocardiology
C.R. Johnson, R.S. MacLeod. In Biomedical Modeling and Simulation, Edited by J. Eisenfeld and D.S. Levine and M. Witten, Elsevier Science Publishers, Elsevier, Amsterdam pp. 283--290. 1992.