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Undergraduate Research Immersion

Research Immersion in Data Science

Data science is an emerging interdisciplinary field whose goal is to extract knowledge and enable discovery from complex data using a fusion of computation, mathematics, statistics, and machine learning. Datasets can be as varied as maps of the universe, MRI images, human genomes, medical records, stock market transactions, educational data, historical texts, infrastructure systems, or website clickstream data.

Over the coming decades, data science is expected to have significant impacts on basic and applied research in the sciences, social sciences, arts and humanities, and engineering as well as impact all sectors of the economy from health care to education, government, transportation, finance, manufacturing, construction, and urban planning. Data science has the potential to improve individual and community health and education; develop smart communities that enable efficient circulation of people, goods, and services; enable informed decision making in public and private sectors; and enhance environmental sustainability and overall quality of life. Given the wide range of applications and potential benefits, the powerful tools and techniques of data science must be used ethically and responsibly.

Students engaged in research immersion in data science can conduct research under the mentorship of a faculty member on a range of topics, including 1) Foundational data science, which involves the development, evolution, or implementation of data science methods, 2) Application of data science techniques, methods, and tools to one or more fields in the physical, life, or social sciences, engineering, arts, or humanities, or 3) The study of the impact of data on society and its institutions.

To prepare for a research immersion in data science, students are encouraged to take at least one semester of computer programming (CS 1000, 1101, 1103, or 1104) and at least one semester of statistics (various options across many departments) in their first year or sophomore year. Students may also need to take other coursework relevant to the research immersion topic in consultation with the faculty mentor.

A list of relevant courses can be found here.

To satisfy research immersion in data science, you must complete the following components:

1. Research Experience (Academic Year or Summer Option)
  • Summer Research Experience Option
    Complete a full-time (40 hours per week) summer research experience in a laboratory of at least 10 weeks in duration. For example, DSI-SRP, VUSRP, NSF REU, other formal summer research program, or full-time paid or full-time volunteer summer research assistantship.


  • Academic Year Research Experience Option
    Complete a course related to data science that provides suitable training for the chosen research direction (at least 3 credit hours); the introductory computer programming course and introductory statistics course cannot count towards this requirement. Complete at least 6 credit hours of undergraduate research in data science.
2. Communication of Research
  • Write a 15-page (minimum) research paper related to the research project.


  • Give an oral presentation of the research project at a poster session (e.g., the Vanderbilt Undergraduate Research Fair or a regional, national, or international conference) (submit an electronic version of the poster) and write a 5-page (minimum) summary and reflection of the research project.

For a list of potential mentors for research immersion in data science, click here.