Congratulations to Alex Lex, who has officially received an NSF CAREER Award.
Enabling Reproducibility of Interactive Visual Data Analysis
Reproducibility and justifiability are widely recognized as critical aspects of data-driven decision making in fields as varied as scientific research, business, healthcare, or intelligence analysis. This project is concerned with enabling reproducibility and justifiability of decisions in the data analysis process, specifically as it relates to visual data analysis. Visualization is an important tool for discovery, yet decisions made by humans based on visualizations of data are difficult to capture and to justify. This project will develop methods to justify, communicate, and audit decisions made based on visual analysis. This, in turn will lead to better outcomes, achieved with less effort and cost. The increasing use of visual analysis tools for decision making will make data analysis accessible to a broad variety of people, as visual analysis tools are generally easier to use than scripting languages and do not require extensive computational and statistical training. This research and its related activities increase accessibility and enhance the data analysis infrastructure for research and education.
New research being conducted at the Scientific Computing and Imaging Institute holds the potential to increase the accuracy of targeted treatments for tumors in the lungs. Currently, motion caused by the patient's breathing introduces motion artifacts when imaging lung tumors. The inherent breathing motion also limits the precise targeting of radiation therapy for treating lung cancer.
ViSUS LLC is one of 16 start-ups selected to exhibit in the NSF SBIR (“America’s Seed Fund”) pavilion at the 2018 CES Eureka Park.
"With access to more than 3,500 financial professionals, 7,000 members of the media, key investors and suppliers, Eureka Park provides startups with a unique opportunity to showcase their ingenuity" [CES].
Yiliang Shi receives honorable mention for the CRA's Outstanding Undergraduate Research Award
Congratulations to Yiliang Shi, who has been selected for honorable mention for the Computing Research Association's (CRA) Outstanding Undergraduate Research Award.
The award program recognizes undergraduate students in North American universities who show outstanding research potential in an area of computing research.
Qi Wu receives Juror Choice Award in the 2017 Teapot Rendering Competition
Congratulations to Qi Wu, who received a Juror Choice Award in the 2017 Teapot Rendering Competition.
The same techniques that generate images of smoke, clouds and fantastic beasts in movies can render neurons and brain structures in fine-grained detail.
Congratulations to Timbwaoga Ouermi, Aaron Knoll, Robert M. Kirby and Martin Berzins, whose paper: "Optimization Strategies for WSM6 on Intel Microarchitectures", received Best Paper at the Fifth International Symposium on Computing and Networking 2017 (CANDAR'17) 2017, in Aomori, Japan.
Air Quality & U, Empowering Citizens through Science
Miriah Meyer and Kerry Kelly talk with KRCL's RadioActive, hosted by Billy Palmer and Lara Jones, on Air Quality and You: Empowering Citizens Through Science.
Low-cost commodity sensors are changing how cities and citizens measure and manage air quality. Through a suite of projects at the U we are building infrastructure that will enable real-time, fine-grained estimates of air quality both inside and outside of homes across Salt Lake City. In this presentation we’ll talk about the science of air quality, the computational challenges of developing rigorous air quality estimates, and our efforts to engage with citizens across the city.
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.