Skip to main content.

Center for Artificial Intelligence and Big Data (CARIDA)

In today’s world of computing, we are undergoing an unprecedented revolution. Exciting advances in artificial intelligence, machine learning, and large scale data collection, storage and management systems have enabled data science and data driven discovery at a scale that has revolutionized areas such as computer vision, natural language processing, autonomous cars, robotics, and genomics. This is made possible by a perfect storm of advances in hardware, sophisticated algorithms and scalable software frameworks. In the years to come, it is expected that these advances will continue to redefine solutions to traditional data-intensive problems in many areas of physical and social sciences, engineering, healthcare, and business.

However, the benefits of this revolution are limited to the few with the necessary expertise – researchers at major research universities, industrial labs and large companies. A number of stakeholders who could benefit from this revolution are at the risk of being left behind, because they are either not aware of the latest research that could be relevant to them, or they lack the necessary expertise to understand and leverage the latest research advances.

The Center for Artificial Intelligence and Big Data (CARIDA) in the College of Engineering of the University of Texas at Arlington focuses on cutting-edge research in large-scale data analysis of very large, diverse data sets that arise in a multitude of today’s real-world applications. The mission of CARIDA is to enable pursuit of grand-challenge problems in artificial intelligence and big data by synergizing the strong expertise in various disciplines across COE, UTA as well as external collaborators, with the goal of establishing UTA as a leader in big data technologies and services. CARIDA will facilitate research collaboration and scientific discovery, enable solutions for emerging applications, as well as educate students with knowledge and skills in data science. CARIDA’s mission aligns with the UTA Strategic Plan and the guiding themes of data-driven discoveries as well as health and the human condition.

graphic image implying big data graphic image implying artificial intelligence graphic image implying machine learning

Goals and Objectives

  • Develop exciting new “grand-challenge” research projects in Artificial Intelligence, Machine Learning, and Big Data (AI/ML/BD) that advance the state of the art.
  • Deliver research that is truly world-class, with publications in premier, high impact journals and conferences, as well as patents and products.
  • Align with UTA’s Strategic Plan and guiding research themes of Data-Driven Discovery and Health and the Human Condition, as well as the research goals and objectives of the College of Engineering.
  • Serve as a hub for COE and UTA faculty, researchers, students as well as external collaborators to engage on AI/ML/BD projects and ideas.
  • Establish visibility by promoting UTA as a leader in AI/ML/BD, which will help facilitate efforts and competitiveness in large grant proposals as well as external institutional and industrial collaborations.
  • Reach out to industry and organizations to understand their AI/ML/BD needs, and partner with them to develop new research projects as well as educational programs.
  • Create innovative AI/ML/BD technologies and help to transfer such technologies into the real world by promoting entrepreneurship and partnerships with industry and organizations.
  • Educate well-prepared students with knowledge and skills in AI/ML/BD and Data Science.

Research Focus

CARIDA will leverage the research expertise and technical leadership of its members to carry out research across the “full stack” of research areas relevant to AI/ML/BD, ranging across (1) Big Data Storage and Management, (2) Artificial Intelligence and Machine Learning, and (3) Applications.

More on CARIDA's Research Focus

Education and Training

Education and research go hand in hand. In addition to its research activities, a significant focus of CARIDA is to support activities related to education and training on AI/ML/BD topics, including but not limited to:

  • Offering introductory tutorials and inspirational lectures to a variety of audiences, including UTA researchers, community partners, and K-12 students
  • Serving an advisory role on related curricula, e.g., UTA’s Master of Science in Data Science (MSDS) degree program
  • Supporting related projects in various settings, e.g., MSDS capstone projects, senior design projects and REU, by facilitating project formulation, student mentoring, industry sponsorships, and so on
  • Supporting faculty and student organizations in carrying out enrichment and outreach activities such as summer camps, hackathons, student workshops, and curricula exhibitions

Recent Educational and Training Activities

External Collaborations

AI/ML/BD are areas of research that are critically dependent on collaborations with industry, nonprofits, governments, as well as other universities. Many of these collaborations lead to successful technology transfer and adoption of research ideas into real-world products. The pathways for these collaborations are diverse, and may include:

  • The Center serves as a clearinghouse of partner-inspired real-world problems that supplies to not only research projects but also capstone and senior design projects, independent study, and REU.  
  • The Center offers free consultation to the community which may lead to sustaining and deeper collaborations.
  • The Center supports external organizations in conducting various activities such as workshops, Hackathons, and summer camps.

CARIDA members have been engaged in various collaborations. A few are listed below. All efforts will be made to nurture and sustain existing engagements, as well as to seek out new collaborative engagements. The eventual goal is to develop a “branding” of the Center as a one-stop hub for organizations seeking know-how and expertise in tackling their domain-specific data-intensive problems.

External Collaborations and Partnerships