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.


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.

September has been good for publications with three papers winning awards.

Jadie Adams, Nawazish Khan, Alan Morris, Shireen Y. Elhabian. Spatiotemporal Cardiac Statistical Shape Modeling: A Data-Driven Approach. The 13th International Workshop on The Statistical Atlases and Computational Modeling of the Heart (STACOM) - MICCAI, 2022, won the “Best Oral Presentation Award.”

Daniel Klötzl, Tim Krake, Youjia Zhou, Ingrid Hotz, Bei Wang, Daniel Weiskopf. Local Bilinear Computation of Jacobi Sets.
Computer Graphics International (CGI), 2022, won the "Second Best Paper Award."

Surojit Saha, Ouk Choi, Ross Whitaker. Few-Shot Segmentation of Microscopy Images Using Gaussian Process. "Best Paper" at 1st International Workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis.

The oneAPI Center will build a portable, scalable, performant ZFP backend using oneAPI and SYCL to advance exascale computing

Manycore and multicore architectures with large memory help with a wide variety of analyses, such as Morse-Smale decomposition to understand ion diffusion characteristics of simulated battery anode materials.

Monday the 19th, Salt Lake City – The University of Utah announces the creation of a new oneAPI Center of Excellence focused on developing portable, scalable, and performant data compression techniques. The Center for Extreme Data Management Analysis and Visualization (CEDMAV) at the University of Utah, in collaboration with the Lawrence Livermore National Laboratory’s (LLNL) Center for Applied Scientific Computing (CASC) will accelerate ZFP compression software using oneAPI open, standards-based, programming on multiple architectures to advance exascale computing.

SCI is excited to announce six new projects that have been funded this past month. We look forward to sharing the research efforts from our amazing faculty and students.

Anna Busatto UURUN19Anna Busatto has been named a recipient of the 2022 Pac-12 Postgraduate Scholarship.

The scholarship is worth $9,000 and annually recognizes up to two student-athletes from each Pac-12 school. Established in 1999, the award honors and financially assists some of the Conference's most outstanding athletes and scholars as they continue their educations and prepare for careers in their chosen industries. Across the Pac-12, scholarship recipients maintained a minimum 3.0 grade-point average and demonstrated a commitment to education, campus and community involvement, and leadership.