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.
Cameron Christensen

Cameron Christensen - Software Developer

WEB 4823
phone (801) 581-8957
fax (801) 585-6513
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supervisor Dr. Tolga Tasdizen

Background

Cameron graduated in 1999 with a B.S. in Computer Science and in 2019 with a M.S. in Computing, both from the University of Utah. He has developed software for use in drafting and design, video compression, product photography, console gaming and advertising.

He joined the SCI Institute in 2010 and has participated in collaborations involving neuroscience, astronomy, global climate study, geosciences, energy research and teaching. He has developed tools to process, assemble, visualize, and annotatate massive microscopy datasets. He has also supported tools for visualization of massive simulation data created by scientists studying clean energy technology.

Cameron is a certified yoga instructor, founded Yoga@SCI after work yoga classes at the SCI Institute, and now teaches at the Eccles Student Life Center here at the U.

Current Responsibilities

Cameron is part of the dSpaceX and ShapeWorks teams helping to organize and maintain extensible software frameworks, adding functionality to these systems, enabling effective communication within development teams and between users, integrating various libraries, and facilitating multiplatform distribution and testing.

Before this Cameron spent several years as part of the research group led by Valerio Pascucci. He contributed to the devlopment of the OpenViSUS Streaming Visualization Framework, including work to process and visualize hierarchical multiresolution data, and integration of OpenViSUS with applications in climate data analysis, combustion simulation, microscopy and education.

Research Interests

  • arbitrarily large data
  • interactive visualization
  • HPC and cloud computing
  • streaming architectures
  • topological analysis
  • ML-based optimization