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.
Dr. Kris Campbell

Dr. Kris Campbell - Postdoctoral

WEB 3616
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supervisor Dr. Sarang Joshi


Dr. Campbell received a BS in Mathematics (University of Wyoming, 2000), an MS in Applied Mathematics (Rensselaer Polytechnic Institute, 2001), and a PhD in Computing with an emphasis on Image Analysis (University of Utah, 2022). His doctoral dissertation provided metric methods for shape analysis of the brain using structural, functional and diffusion MR imaging modalities.

Prior to pursuing his doctoral degree, Kris joined the SCI Institute in 2009 as a software developer. He contributed to a variety of open-source image processing and visualization projects, including working with Dr. Tom Fletcher to create a longitudinal DTI pipeline to preprocess DWI image and segment white matter tracts based on seed regions.

Prior to joining the SCI Institute, he was a software engineer and systems engineer (Raytheon, 2002-2009) implementing and refining signal processing algorithms in a distributed processing environment.

Current Responsibilities

Dr. Campbell is developing methods for longitudinal analysis of brain shape by integrating information from structural and diffusion MRI.

Research Interests

  • Understanding how structure and function of the brain relates to cognitive ability by analyzing the shape and organization of brain regions.
  • Exploring the interplay between visualization and data analysis, providing tools that combine the strengths of both to enable analysts to gain new insights into their data
  • Sharing data, methods, software and resources to improve the quality, reproducibility, and efficiency of open science.
  • Manifold geometry
  • Image processing
  • Systems design