Overview and Goals



Statistics and Data Sciences, as a discipline, has grown and expanded tremendously in recent years making it possible to get a deeper, broader and more accurate understanding of what data are trying to tell us. IDSC exists in part to help faculty and students take advantage of what contemporary tools and techniques of data analysis have to offer.

Let us communicate beyond the boundaries of disciplines and colleges and together understand latest trends in data science including big data trends and research, learn successful cases and move forward with creating research beyond the disciplinary boundaries. It is a win-win for everyone.


The vision of the Interdisciplinary Data Sciences Consortium is to foster and create  best resources for data analysis including big data analytics in the state of Florida, and lead  the University’s Data intensive research and education with involvement of  students and faculty.


The mission of the IDSC is to provide and advance interdisciplinary data science expertise and training to students, USF community, state and country through fostering scholarly environment in all aspects of Statistical Sciences and its application.


Overall goal is to discover, develop and apply data analytics solutions to big data problems such that the random data is transformed into knowledge and useful products.

  • Create opportunity for interdisciplinary data science education for students.
  • Conduct joint research and compete for different types of funding.
  • Create database for truism, environmental, medical, etc.
  • Develop big data analytics
  • Use data to model, evaluate, and forecast.

Core Values

IDSC embraces following core values:

  • Excel in data related research with accountability and integrity.
  • Promote cooperation among people from different disciplines and backgrounds.
  • Serve as a catalyst for change.

Action plan

  • Biweekly interdisciplinary seminar
  • Offer short courses and workshops
  • Write joint grant proposals
  • Train grad and post docs in multidisciplinary statistics and big data
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