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.

alex lexDr. Alexander Lex, School of Computing

Dr. Lex received his Bachelor's, Master's, and PhD degrees from the Graz University of Technology. For the past three years he was a Postdoctoral Fellow and Lecturer at the Harvard School of Engineering and Applied Sciences. In 2011 he completed a research internship at the Computational Genomics Lab at the Harvard Medical School.

He develops interactive data analysis methods for experts and scientists. His primary research interest is interactive data visualization and analysis, especially applied to molecular biology and pharmacology. His research is driven by the observation that there are many data analysis challenges that require human reasoning and cannot be solved automatically. He is also interested in Human Computer Interaction and Bioinformatics.

He is a co-founder and leader of Caleydo, which is both, open source software that can be used by life science experts to visualize biomolecular data and pathways, but also a platform for implementing prototypes of radical visualization ideas.

Dr. Lex has received numerous awards, including three best paper or honorable mention awards at IEEE InfoVis, the premier conference for information visualization, and a best dissertation award from his alma mater. He is on the program committee for IEEE InfoVis and BioVis, is a poster chair at BioVis, and a program chair at the Visualization in Data Science Symposium.

At the University of Utah, Dr. Lex will be on the faculty of the School of Computing. His goal will be to develop novel interactive data analysis methods in support of addressing the challenges of big data, by tightly integrating visualization with algorithms, statistics, and machine learning.

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Visualization of experimental data in connected biological pathways.

akil narayanDr. Akil Narayan

Department of Mathematics

Dr. Narayan received his Bachelor's Degree from Northwestern University, and his Master's and PhD degrees from Brown University. He served as a postdoctoral researcher at Purdue University until starting an Assistant Professorship in the Mathematical Department at the University of Massachusetts Dartmouth.

His primary research interests lie in approximation theory and methods, sparse and regularized representations, mathematical shape analysis, high-order numerical methods, and data assimilation. He applies these methods to parameterized systems, high-dimensional approximation, and hierarchical model simulations. Dr. Narayan is receipient of a 2015 Young Investigor Program Award from the Air Force Office of Scientific Research.

Dr. Narayan will join the SCI Institute as a faculty member in the Department of Mathematics.

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Modeling flowchart diagram for reconciling multiple predictions and data sources.

For more information, contact Chris Johnson, Ph.D. - Director
Scientific Computing and Imaging Institute, University of Utah
This email address is being protected from spambots. You need JavaScript enabled to view it. (801) 581-7705