Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Large scale visualization on the Powerwall.
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.
Dr. Mani Razi

Dr. Mani Razi - Postdoctoral Fellow

WEB 2654
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supervisor Dr. Mike Kirby


Dr. Mani Razi is a postdoctoral fellow in the Scientific Computing and Imaging Institute (SCI) at the University of Utah since October 2016. He earned his Ph.D. degree in Aerospace Engineering from the University of Oklahoma in May 2015 and prior to joining SCI was a postdoctoral research associate in the department of Aerospace and Mechanical engineering at the University of Oklahoma.
Dr. Razi received a B.Sc. in Mechanical Engineering from Islamic Azad University in Tehran, Iran and his M.Sc in Aerospace Engineering from Tarbiat Modares University in Tehran, Iran in 2003 and 2006, respectively.

Current Responsibilities

Performing research in the development, implementation and application of computational and applied mathematical methods to multiscale algorithms developed at both the continuum level and molecular dynamics level. I work closely with SCI Institute researchers and external collaborators to integrate research into SCI Institute software applications and apply this software to compelling problems in science and engineering.

Main responsibilities include:

  • Development of applied mathematics techniques for various multiscale systems
  • Implementation and evaluation of these methodologies within collaborative codes bases
  • Scientific interaction between the Applied and Computational Mathematics and Uncertainty Quantification Group and other engineering areas within SCI's Multiscale Modeling Center (MSME)

Research Interests

  • Incorporating uncertainty quantification approaches in numerical analysis of dynamic systems to obtain more efficient and reliable solutions
  • Developing a computationally efficient and highly accurate solver for hyperbolic partial differential equations with applications in CFD and statistical analysis
  • Analysis of fluid-structure interaction in engineering systems using coupled computational fluid and structural dynamics approaches
  • Application of Aerodynamic theories in lift, drag and aerodynamic moments calculation