Visualizing Big Data

Through advanced computing and our visualization facilities, the Center for Visual & Decision Informatics creates decision-making environments (DME) that allow users to explore, customize and, ultimately, gain better insight into their information.

A Big Data Sciences Collaboration Center

Established in 2012, the Center for Visual and Decision Informatics works in partnership with government, industry, and academia to develop the next-generation visual and decision support tools and techniques that enable decision-makers to significantly improve the way their organization's data is organized and interpreted. 

University Partners 

                

 

                  

 

Accomplishments

  • Completed 128 IAB – funded projects in 10 years with 219 undergrad and graduate students 
  • Total center funding topped $17.2 million in Y1 -Y10
  • Nominated by industry for 2 technology breakthroughs
  • Published 274 CVDI-related papers, filed 111 invention disclosures, 28 patents and 6 licensing agreements
  • Organized first ever IEEE international conference on Big Data
  • Launched two annual hackathons - UL Lafayette's CajunCodeFest and Drexel University's Philly Code Fest
  • Recognized as the first NSF IUCRC to focus on “Big Data”
  • First NSF IUCRC center in Louisiana
  • Successfully added an international academic research site in 2015 - Tampere University in Finland
  • Moved to Phase II of the IUCRC program on March 1, 2017, adding the University of Virginia, StonyBrook University and the University of North Carolina at Charlotte

 A National Science Foundation Industry University Cooperative Research Center (IUCRC)

CVDI is part of NSF IUCRC program that promotes high-quality industry relevant research and direct technology transfer of ideas, research results and technology to U.S. industry. It brings a consortium of researchers and students across multiple universities to advance research and innovation in big data with respect to Internet of Things – specifically how large scale multidimensional datasets are analyzed and interpreted using advanced data mining, and visual and perceptual techniques for decision makers. 


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