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.


1000014743Congratulations to Jake Bergquist who received the Heart Rhythm Society fellowship award. This is a one year, $50,000 fellowship to support research in cardiac electrophysiology.

1607352443 1We are happy to announce that Manish Parashar is the recipient of the 2023 Achievement Award in High Performance Distributed Computing for pioneering contributions in high performance parallel and distributed computational methods, data management, in-situ computing, and international leadership in cyberinfrastructure and translational computer science.

By Despina Giannopoulos
March 10, 2023

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Youjia Zhou is a computing Ph.D. candidate at the University of Utah working to help scientists and mathematicians with their knowledge-discovery process through practical visual analytics systems. Her research focuses on large and complex data, coupling theoretical analysis with interactive visualization to help users quickly gain insights from complex graphs and hypergraphs.

Over 200TB of NASA climate data is now accessible through the collaboration between Seal Storage Technology and the University of Utah's Scientific Computing and Imaging Institute (SCI), enabling researchers around the world to access and visualize the data with zero egress fees.

TORONTO and SALT LAKE CITY, April 12, 2023 /CNW/ - In an effort to democratize data access, decentralized cloud storage provider Seal Storage Technology and the University of Utah's Scientific Computing and Imaging Institute (SCI) announced today that over 200 terabytes  (TB) of OpenViSUS IDX NASA  atmospheric wind velocity and ocean current datasets are now openly available to researchers globally. The data will be accessible via a Jupyter notebook, which is a digital document that makes it easy to access and visualize data by combining text, code, and visualizations in a single medium. This project is part of SCI's participation in The National Science Data Fabric  (NSDF), a trans-disciplinary approach to integrated data delivery and access, democratizing data-driven scientific discovery through shared storage, networking, computing, and educational resources.

pascucciThe Office of the Vice President for Research (VPR) has selected SCI faculty member Valerio Pascucci as a 2022-2023 Distinguished Research Award (DRA) recipient. The DRA is designed to shine a spotlight on the outstanding achievements of University of Utah research faculty.

“Valerio is an outstanding scientist, leader, and mentor. He is integral to the vision and mission of the SCI Institute. He has made significant research contributions and long-lasting scientific and societal impacts,” said SCI Director, Manish Parashar. “We are delighted that the University of Utah has recognized Valerio’s contributions by awarding him the Distinguished Research Award.”

fdbf489aa053b328f6cf5c8a 313xautoPenny Atkins, PhD has been named associate director of the One Utah Data Science Hub, which connects the Data Exploration and Learning for Precision Health Intelligence (DELPHI) Initiative, the Data Science and Ethics of Technology (DATASET) Initiative, and the Utah Data Science Center to expand data science research, education, outreach, infrastructure, and datasets at the University of Utah.

Sage sensors monitor environment, support ‘edge AI’

Jesse Drake - University Information Technology


Smokey Bear is mostly right—you can help prevent wildfires—but it’s not all on you. Using fire-resistant building materials, establishing vegetation-free “ignition zones,” and avoiding fire-related activities when it’s hot, dry and windy are actions that, ideally, we all can take.

The scientific community, too, has a preventive role to play around natural disasters, urbanization and climate change. Recent advances in this area, like attempts to predict fire behavior before it becomes unmanageable, are the result of an ambitious project to build a continent-wide network of intelligent sensors that monitor environmental changes.


Congratulations are in order for several SCI faculty who took to the awards stage at the IEEE Visualization conference this year in Oklahoma City. Valerio Pascucci was not only awarded the IEEE VGTC Visualization Technical Achievement Award, but was also inducted into the IEEE Visualization Academy. The Visualization Academy is a prestigious academy that highlights the accomplishments of the leaders in the field. These awards are limited in number, and recognize those in the field who exceed or augment the criteria of existing VGTC awards. Furthermore, Valerio, along with co-authors Atilla Gyulassy, Peer-Timo Bremer, and Bernd Hamann received the Scientific Visualization 14 year Test of Time Award for the paper: A practical approach to Morse-Smale complex computation: Scalability and generality.

valerio w awardsThe 2022 VGTC Visualization Technical Achievement Award goes to Valerio Pascucci for his seminal contribution in using topology for visualization and analysis of data.

Valerio Pascucci is the John R. Parks Inaugural Endowed Chair of the University of Utah, a Professor of Computer Science in the School of Computing, a faculty member of the Scientific Computing and Imaging Institute, and the Founding Director of the Center for Extreme Data Management Analysis and Visualization (CEDMAV) at the University of Utah. He received a Ph.D. in computer science from Purdue University after moving from Italy to the US. Valerio’s Ph.D. research was titled “Multi-dimensional and multi-resolution geometric data-structures for scientific visualization” and investigated the effective use of visualization techniques to enable the interactive, intuitive exploration of big scientific data.

bergquist2This year at computing in cardiology I presented two talks, both on the subject of uncertainty quantification in the context of electrocardiographic imaging. Uncertainty quantification is a technique to understand how models such as those we use to simulate or estimate the activity of the heart respond to errors or variability in the inputs to these models.

Congratulations to Chris Johnson (SCI) and Daniel Turner (Sandia National Laboratory) on their recently funded project "Ab Initio Visualization for Innovative Science."

This project aims to establish a theoretical framework to design scientific experiments starting with the visualization of the results (in this case, visualization of data represented as images) and working backwards to optimize experimental parameters to drastically increase information gain and decrease costs. The goal of this work is to use photo-realistic, model-based, synthetic visualization to enable a drastic leap forward for image-based experiments of complex or extreme events. The combination of optimal experimental design theory and post-optimality sensitivity analysis will be used to maximize scientific discovery in service of decision-making. Post-optimality sensitivity analysis will also elucidate model inadequacies and sources of bias by probing the discrepancies between the ab initio visualization (expected or speculative results) and the actual results of the experiment, in addition to guiding analysts to the most important features responsible for the phenomena observed in the visualization.