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 how their organization's data is organized and interpreted. After two successful phases as a National Science Foundation Industry University Cooperative Research Center, CVDI has graduated to an independent center. 

University Partners 






  • 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 graduate of the National Science Foundation Industry University Cooperative Research Center (IUCRC) Program after two successful phases.

CVDI was part of the NSF IUCRC program that promotes high-quality industry-relevant research and direct technology transfer of ideas, research results, and technology to U.S. industry. The consortium of researchers and students across multiple universities advances 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. 

Official Website