Project Summary

Data science and analytics is an emerging transdisciplinary area comprising computing, statistics, and various application domains including medicine, nursing, industry and business applications among others. A significant shortcoming of the current graduate curricula in the U.S. is that scientists and engineers are well trained in their own areas of specialty but lack the integrative knowledge needed for new scientific discoveries and industry applications made possible by data science and analytics. The National Science Foundation Research Traineeship award to Florida Atlantic University will address these shortcomings by proposing a new model of convergence education through experimental learning. Transdisciplinary education brings integration of different disciplines in a harmonious manner to construct new knowledge and uplift the student to higher domains of cognitive abilities and sustained knowledge and skills. The traineeship anticipates providing a unique and comprehensive training opportunity for one hundred twenty five graduate students (125), including thirty five (35) funded trainees. Thirty faculty members from five colleges and ten departments will participate in the program. The program has the potential to have a significant impact on training practices for future data science professionals.

Primary training elements of the curriculum will include the development of normalization courses, the creation of different testbeds for the various application domains, boot-camps, in-depth elective courses, and professional workshops. Normalization courses will be used to address various background of students entering the program. The convergent research themes will focus on three data science and analytics areas: (i) medical and healthcare applications, (ii) industry applications, and (iii) data science and AI technologies. To address these, the goal is to create a curriculum for graduate students in data science and analytics, where each course will be developed by at least two faculty members from two different disciplines. In order to integrate research and training, multiple testbeds for different application domains will be developed in a newly created Data Science and Artificial Intelligence Laboratory. Each testbed, which relates to a research project, will include a computer platform, software tools, and a set of learning modules. Research projects will be formulated jointly with industry partners who are members of the NSF Industry/University Cooperative Research Center CAKE at FAU. The program will produce graduates with technical depth and understanding of data science technologies and applications.