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.
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.