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The opinions, findings, and conclusions or recommendations expressed are those of the Center author(s) and do not necessarily reflect the views of the National Science Foundation.

Center Overview

The Center for Visual and Decision Informatics (CVDI) conducts multidisciplinary, cross-institutional research to develop the visual and decision support tools and techniques that allow leaders to improve the way their organization's data are organized and interpreted. CVDI develops visualization and data analytics techniques for sectors including government, health care, sustainability, transportation, commerce, and finance. As part of its efforts, CVDI recognizes the importance of research related to ethics, accountability, and transparency, when data analytics has to function in increasingly complex and emerging contexts such as augmented intelligence and cybersecurity.

CVDI seeks to transform data into insights. Its goals are to:

  • Develop the next-generation technologies in data science, Big Data, and analytics, including visual analytics, augmented intelligence, and decision informatics.
  • Address data science and Big Data challenges facing industry and government and provide practical solutions in a broad range of market sectors.
  • Work collaboratively with industry and government partners to unleash the transformative potential and associated opportunities of Big Data and data science for the benefit of society.
  • Produce highly trained students with practical hands-on skills in data science and Big Data.
  • Inform policymakers, government, and industry about the significance of data science and Big Data.

Vision Statement. The Center for Visual and Decision Informatics strives to become a world leader for creating a win-win partnership between industry and academia in the big data space. UL Lafayette, Drexel University, SBU, UVA, UNCC, and TAU along with other future academic partners, will cooperate with the objective to accelerate research, innovation, technology transfer, and student training in the big data space. The purpose of this concerted effort is to continue the ongoing efforts and make CVDI the most sought after research and development consortium for next-generation visual analysis and decision support tools and techniques.

Mission Statement. The core mission of CVDI in Phase II is to (1) conduct multi-disciplinary, cross-institutional pre-competitive research and develop the next-generation technologies in data science, big data, analytics, including visual analytics, augmented intelligence, and decision informatics, (2) address data science and big data challenges facing industry and government and provide practical solutions in a broad range of market sectors, (3) work collaboratively with industry and government partners to unleash the transformative potential and associated opportunities of big data and data science for the benefit of society, (4) produce highly-trained students with practical hands-on skills in data science and big data, and (5) inform policy makers, government, and industry about the significance of data science and big data.

Phase 2 - CVDI Goals

1. Become a world leader in big data and data science by creating exceptional core competencies across multiple areas.

2. Create a network of diverse and complementary research sites, both in the US and abroad, that deliver extensive technical expertise to industrial partners and the research community.

3. Accelerate the creation and transfer of technology to industry and commercial products.

4. Attract high quality student talent, and produce future workforce that has the potential to benefit local, national and global economy.


  • University of Virginia
  • Tampere University
  • University of Louisiana, Lafayette
  • University of North Carolina, Charlotte
  • Drexel University
  • Stony Brook University
View Center Website

Center Personnel

Don Davis
Center Evaluator
+1 757 576 8660

Matthew Delcambre
Center Staff
+1 337 482 0692

Stephen Adams, Ph.D.
Center Staff
+1 757 870 4954

Doug Hague, Ph.D.
Center Staff
+1 704 562 6867

Raju Gottumukkala, Ph.D
Center Staff
+1 337 482 0632

Rong Zhao, Ph.D.
Center Staff
+1 631 632 4627

Xiaohua Hu, Ph.D.
Center Co-Director
+1 215 895 5884

Moncef Gabbouj, Ph.D.
Center Co-Director
+358 40 0736613

Vijay Raghavan, Ph.D.
Center Director
+1 337 280 8451

Arie Kaufman, Ph.D.
Center Deputy Director
+1 631 632 8428

Mirsad Hadzikadic, Ph.D.
Center Co-Director
+1 704 687 8643

Peter Beling, Ph.D.
Center Co-Director
+1 434 982 2066

Research Focus

Synergistic aspects of complementary data science and big data research initiatives

The Center's research program focuses on synergistic aspects of complementary data science and big data research initiatives in the areas of data acquisition and management, analytics, visualization & human interaction, and applications to drive innovation in visual and decision informatics. The research topics facilitate analytical reasoning through interactive visualization to enable decision makers in government and industry to fundamentally improve the way their organization's information is interpreted. Topics in data management include big data platforms, knowledge organization, data fusion and integration, parallel processing of massively large datasets, and green computing. The research topics within the analytics domain include visual analytics, predictive analytics, augmented intelligence, data summarization, deep learning, complex systems analysis, evolutionary optimization, agent-based models and simulation, privacy-preserving learning, and meta-learning. Visualization and human computer interaction topics include interactive visualization, human computer interaction modeling, cognitive assistance, and immersive analytics.

The Center focuses on work that cuts across these technical areas and develops visualization and data analytics techniques in the context of important application sectors, such as government, healthcare, sustainability, transportation, commerce, and finance. In addition, CVDI recognizes the importance of research related to the ethics, accountability and transparency, when data analytics has to function in increasingly complex and emerging contexts such as augmented intelligence, digital twins and cybersecurity. As an industry/university cooperative research center, the industry and academic partners believe that these use-inspired research projects seek to deliver inventions and new uses of visualization and data analytics to a variety of domains with a goal of transforming data into insights.


Drexel University

Drexel is a world-class comprehensive research institution committed to use-inspired research with real-world applications, and the University's research activities result in more than $110 million in annual expenditures for sponsored projects.

Research at Drexel is driven by faculty from all disciplines. Medical and health sciences research complements traditional strengths in engineering, biotechnology, basic science, information science, and business, alongside innovative scholarship in media arts and design, the social sciences, education, and law. The Office of Research at Drexel University is committed to facilitating these research efforts.

Clear examples of the University's interdisciplinary approach to research can be seen in efforts to meet emerging national imperatives to upgrade the transportation infrastructure, move alternative energy sources into the mainstream, and invent the means to improve medical care while reducing its costs. The University has also established major research initiatives in engineering cities, plasma medicine and biology, and neuroengineering.

The College of Computing and Informatics at Drexel provides access to a variety of specialized facilities, including a large server IBM e1350 Linux Cluster dedicated to research use. It contains: an IBM eServer Cluster 42U Enterprise Rack; 15 IBM x335 servers (computing nodes) containing: Dual 2.8Ghz Intel Xeon Processors, 1.5GB PC2100 ECC DDR SDRAM 100Mhz Bus, 512KB L2 Cache, 40GB Fixed IDE; an IBM x345 server; an IBM DS400 SAN Storage Subsystem; and 14 300GB 10000rpm Ultra320 SCSI Hot Swap drivers = approximately 3 TB on 2 RAID-5 Volumes.

Stony Brook University

Stony Brook University is going beyond the expectations of what today's public universities can accomplish. Since its founding in 1957, this young university has grown to become one of only four University Center campuses in the State University of New York (SUNY) system with more than 25,700 students, 2,500 faculty members, and 20 NCAA Division I athletic programs. Our faculty have earned numerous prestigious awards, including the Nobel Prize, Pulitzer Prize, Indianapolis Prize for animal conservation, Abel Prize and the inaugural Breakthrough Prize in Mathematics.

The University offers students an elite education with an outstanding return on investment: U.S.News & World Report ranks Stony Brook among the top 40 public universities in the nation. Its membership in the Association of American Universities (AAU) places Stony Brook among the top 62 research institutions in North America. As part of the management team of Brookhaven National Laboratory, the University joins a prestigious group of universities that have a role in running federal R&D labs.

Stony Brook University is a driving force in the region's economy, generating nearly 60,000 jobs and an annual economic impact of $4.65 billion. Our state, country and world demand ambitious ideas, imaginative solutions and exceptional leadership to forge a better future for all. The students, alumni, researchers and faculty of Stony Brook University are prepared to meet this challenge.

Tampere University

Tampere University (TAU) is at the leading edge of technological development and a sought-after collaboration partner among the scientific and business communities. We educate skillful graduates to serve the needs of society. Our University is a fertile breeding ground for innovations and new research- and knowledge- based companies. We generate new knowledge and expertise for the benefit of society. We foster the well-being of people and the environment through research and education. We develop technologies that reshape the competitive landscape of Finnish industry.

Technology is the key to addressing global challenges. TAU generates research-based knowledge and competence for the benefit of society.

TAU combines a strong tradition of research in the fields of natural sciences and engineering with research related to industry and business. Particular strengths include the interaction between fundamental and applied research, broad international networks and high-quality research projects that cut across departmental and disciplinary boundaries.

Signal processing, optics and photonics, intelligent machines, biomodelling and the built environment have been identified as the University's leading-edge fields of research in Research Assessment Exercise in 2011. Within its leading-edge fields, TAU aims to rank among the world's leading research institutions.

University of Louisiana at Lafayette

The researchers at the University of Louisiana at Lafayette have access to specialized equipment that includes cloud computing infrastructure, virtual reality environments, and big data enterprise storage capabilities. Additional computational resources are available at the Louisiana Optical Network Initiative, which provides one of most powerful distributed supercomputer resources available to any academic community with over 85 teraflops of computational capacity.

CVDI has access to the Science DMZ infrastructure at the University that delivers a next-generation packet transport service with traffic identification, security, and application controls. The Science DMZ has 80GE (dual 40GE) Science DMZ backbone connectivity, with the ability for researchers to connect their systems at 10Gbps and access data at high connection speeds.

Some of the laboratories that the UL Lafayette CVDI researchers utilize include: Laboratory for Internet Computing (LINC), Cyber Physical Systems Lab, CACS Virtual Reality Lab, Network Science Research Group, and Watershed Flood Center Graduate Lab.

University of North Carolina at Charlotte

The University of North Carolina at Charlotte has created centers of excellence in data visualization, visual analytics, statistics, machine learning, artificial intelligence, Geographic Information Systems, complex adaptive systems, systems science, cyber security analytics and energy analytics. These centers form the core of the School of Data Science (SDS) at UNC Charlotte. SDS is built on the foundation laid by its precursor, the Data Science Initiative, building on its industry-university-state partnership that highlighted an intramural engagement touching virtually every academic and research entity on-campus.

SDS provides an effective solution to the challenge of "Big Data" by creating education, training and research programs in data science and analytics integrated with business and industry expertise while integrating analytic teams with domain experts to address challenges. The surrounding hub of top financial services, energy, retail sales and distribution, advanced manufacturing, and technology companies provides an ideal environment to utilize this suite of skills only an urban research university can accommodate-Big Data understanding and innovation, business acumen, and technical mastery.

University of Virginia

The UVA site of CVDI will pursue a research agenda that features an integration of control, decision, and systems modeling concepts with statistical methods, machine learning and pattern recognition. Areas of concentration include cognitive assistance, information retrieval, natural language processing, latent structure learning, reinforcement learning, deep learning, data fusion and distributed learning, spatio-temporal models, and agent-based models and simulation. A distinguishing characteristic of the UVA site research agenda is an emphasis on prescriptive modeling and the use of data in the context of decision making in complex systems. Specific research directions identified for initial projects include: (1) Systemic risk analytics addressing fragility and shock propagation in networks, financial or otherwise; (2) Cognitive assistance analytics that help humans interact with complex socio-technical systems, such as the law; and (3) Privacy and anonymity analytic methods that preserve these quantities. Current site members include companies the fields of manufacturing, IoT and sensing, data privacy and security, finance and banking, national defense, and media.

UVA faculty participation includes more than a dozen members from the three computing and informatics departments Computer Science, Electrical and Computer Engineering, and Systems and Information Engineering as well as members the College of Arts & Science (Psychology), McIntire School of Commerce, School of Medicine, and School of Law. This faculty interest reflects the critical importance of data science across all disciplines, as well as the breadth of UVA's academic and professional degree programs. The UVA CVDI site is a Center of Excellence within UVA's Data Science Institute, which supports all aspects of data science across the university with a rich array of computational resources that includes a secure cloud for analytics on medical patient and other sensitive data. UVA has a deep commitment to industry-sponsored research, which accounts for 20% of the total activity in School of Engineering and Applied Science, and a rich history of engaging with the I/UCRC program that includes current or past membership in the Laser Center, NGeNE, WICAT, and BWAC. Other major industry research relationships include being one of three U.S University Technology Centers for Rolls Royce Corporation and being a founding university member of the Commonwealth Center for Advanced Manufacturing, which has more than 30 industry members. Founded in 1836, the University of Virginia School of Engineering and Applied Science is the third oldest engineering school at a public university in the U.S., with a distinguished faculty and a student body of 2,300 undergraduates and 615 graduate students.