Research & Thematic Labs

Research & Thematic Labs

Data Science Research Community

Coffee Connections TAMIDS’s Data Science Coffee Connections program facilitates cross-departmental interactions among Texas A&M researchers interested in Data Science. Through this program, TAMIDS provides a platform that each month randomly pairs participants, who can then arrange a 30-minute meeting to exchange ideas. It’s entirely up to you where you take your conversation.

Bring-Your-Own-Data The Bring-Your-Own-Data (BYOD) Online Consultancy program helps researchers formulate approaches to their data science research projects and assists with code development to take advantage of the latest data analytics methods and high-performance computing facilities. The structure is flexible, personalized, and free.

Thematic Labs

Exploring themes in Data Science, Artificial Intelligence, and Machine Learning.

TAMIDS establishes new labs that develop knowledge, resources, and community around a thematic area of data science, encompassing research, education, and outreach. There are dozens of researchers across our eight (8) Thematic Labs working to strengthen Texas A&M’s research, improve data science literacy, and tackle challenges impacting society. TAMIDS provides support for outreach activities, post-doctoral researchers and graduate students working on lab research projects, and creating collaboration opportunities.

What do Thematic Labs Do?

  • Conduct collaborative pilot research projects
  • Develop training, tutorials, case studies, and for-credit courses
  • Establish research and education data resources
  • Organize workshops and seminar series
  • Recruit additional members
  • Involve students in Lab research and education activities
  • Develop proposals for funding based on the work of the Lab

For more information about how the labs were created, visit Thematic Data Science Labs Program.

Agriculture Smart Data Lab

The advent of advanced instrumentation, detailed environmental data, and precision treatment capabilities in agriculture, provides new and compelling opportunities to apply Data Science to Agricultural Engineering. The Agricultural Smart Data Lab uses machine learning techniques to model the influence of plant genetics, the environment, and treatment factors on plant growth, develops algorithms that adaptively optimize treatment over the growing season to meet goals for yield and cost, and embodies these algorithms in decision support systems that can deliver practical recommendations for crop treatment based on available knowledge.

Data Justice Lab

The Data Justice Lab at Texas A&M University is a multidisciplinary research lab dedicated to Data for Social Justice. The mission of this lab is to develop knowledge, resources, and community around Data for Social Justice. It brings together computational data scientists and social justice-oriented social scientists to address the role of data sciences in social issues in various domains such as health, education, built environments, crisis management, and finance. 

Digital Twin Lab

The TAMIDS Digital Twin Lab aims to build up the research capacity on Digital Twins (DTs) at Texas A&M and develop innovative computing and networking technologies and efficient theory/data-driven modeling methods to speed up the creation and deployment of DTs for a wide spectrum of real world applications. The lab also actively develops and engages in education and training programs to teach and promote DT technologies across the Texas A&M System.

Knowledge Development Lab

Data Science is a multidisciplinary field that utilizes statistics, data analysis, machine learning, algorithms, software, and computing systems to extract information, acquire knowledge, and gain insights into the underlying context from which data is generated. TAMIDS leads and supports the development of knowledge and expertise in Data Science (and the related areas of Machine Learning and Artificial Intelligence) through multiple programmatic and research activities.

Operational Data Science Lab

The Operational Data Science Lab is a joint enterprise between the Texas A&M Institute of Data Science and the Texas A&M Center for Geospatial Science, Applications, and Technology to develop partnerships with operational organizations in Texas A&M that capitalize on institutional data investments to improve campus operations and achieve research and academic goals, and support Texas A&M researchers working on operational problems.

Scientific ML Lab

The SciML Lab at Texas A&M fosters a collaborative community of researchers spanning various disciplines, dedicated to developing physics-aware machine learning algorithms. As part of the Texas A&M Institute of Data Science, the lab accelerates education in Scientific Machine Learning through courses, seminars, workshops, and case studies.

Urban AI Lab

The Urban AI Lab creates digital twins and VR/AR simulations for cities and regions, aiming to enhance understanding of urban infrastructure and improve resilience. Additionally, the lab develops and supports free open-source tools for reproducible urban problem-solving, offering dynamic analysis of real-time built environments and testing scenarios for sustainable growth and climate action.


The VIVID Lab for Visceral Inter­sensory Visualization & Information Design explores how both experts and non-experts can interact with the analyses of Data Science, through systems and technologies to produce both visible and tangible representations. The lab takes visualization beyond the traditional notion of a visual display and incorporates new mechanisms, including sensors, AR/VR, craft, and 3D printing and fabrication.

Closed Programs