Valerio and Kree Receive IEEE Visualization 15 Year Test of Time Award
Congratulations to Valerio Pascucci and Kree Cole-McLaughlin on receiving the IEEE Visualization 15 Year Test of Time Award for their paper "Efficient computation of the topology of level sets."
Using topological approaches to analyze level sets from scalar field has been an important branch of methods in the SciVis community. While the theories of contour trees had been known prior to this paper, efficient and robust computation of contour trees and other topological features from a discrete data set has been a challenge. In this paper, the authors provided a detailed account of the implementation of contour tree computation. The improved efficiency and the enhanced feature namely the Betti number makes the topological approach more practical and accessible to the scientific community. Considering the citation counts, the importance of the work, and the potential impact to the application areas, the SciVis Test of Time award committee selected this paper as the 2002 SciVis Test of Time award winner.
Chuck Hansen Receives the 2017 IEEE Visualization Career Award
Congratulations to Charles (Chuck) Hansen, who received the 2017 IEEE Visualization Career Award. Dr. Hansen is received the award for his contributions to large scale data visualization, including advances in parallel and volume rendering, novel interaction techniques, and techniques for exploiting hardware; for his leadership in the community as an educator, program chair, and editor; and for providing vision for the development and support of the field.
The Scientific Computing and Imaging (SCI) Institute and the Center for Extreme Data Management, Analysis, and Visualization (CEDMAV), in collaboration with ARUP Laboratories and the University of Utah, Department of Neurobiology and Anatomy, have developed ViSOAR--a multi platform visualization application for accessing and processing very large imaging data.
The SCI Institute, in partner with the School of Computing, is excited to announce the acquisition of an Nvidia DGX-1 deep learning system. This will be a shared resource that will be made available freely to all campus researchers interested in deep learning, machine learning and related areas.
Big data and machine learning are major factors shaping research and innovation now and will continue to be so in the foreseeable future. Deep learning represents the state-of-the-art in machine learning and data analysis.
Research with Fluorender highlighted on the NIH Director's Blog. Posted on July 27, 2017 by Dr. Francis Collins
Twice a week, I do an hour of weight training to maintain muscle strength and tone. Millions of Americans do the same, and there's always a lot of attention paid to those upper arm muscles—the biceps and triceps. Less appreciated is another arm muscle that pumps right along during workouts: the brachialis. This muscle—located under the biceps—helps your elbow flex when you are doing all kinds of things, whether curling a 50-pound barbell or just grabbing a bag of groceries or your luggage out of the car.
Research Initiative Seeks to Understand Neural Pathways in Deep Brain Stimulation
The University of Utah Neuroscience Initiative recently announced Christopher Butson, PhD, Associate Professor in Bioengineering and the Scientific Computing and Imaging Institute, was awarded funding for his project, "Differentiating Neural Circuits Modulated During Therapeutic Versus Ineffective Deep Brain Stimulation".
University of Utah bioengineers detect early signs of damage in connective tissues such as ligaments, tendons and cartilage
By the time someone realizes they damaged a ligament, tendon or cartilage from too much exercise or other types of physical activity, it's too late. The tissue is stretched and torn and the person is writhing in pain.
But a team of researchers led by University of Utah bioengineering professors Jeffrey Weiss and Michael Yu has discovered that damage to collagen, the main building block of all human tissue, can occur much earlier at a molecular level from too much physical stress, alerting doctors and scientists that a patient is on the path to major tissue damage and pain.