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ֱAwarded $2.4 Million NSF Grant to Train Data Scientists

NSF, National Science Foundation, Grants, Data Science, Engineering, Medicine, Nursing, Healthcare, Big Data, Artificial Intelligence, Machine Learning


By gisele galoustian | 9/10/2020

Researchers from ֱ’s in collaboration with FAU’s , , and , have received a five-year, $2.4 million grant from the National Science Foundation to train graduate students in data science technologies and applications. Data science and analytics is an emerging transdisciplinary area encompassing computing, statistics and various application domains that include medicine, nursing, and industry and business applications among others.

Although scientists and engineers are well trained in their own areas of specialty, there is a lack of integrative knowledge needed for new scientific discoveries and industry applications made possible by data science and analytics.  

“Big data and data science is a burgeoning field that requires a highly-skilled workforce representing many disciplines who are adept at gathering, interpreting and analyzing massive amounts of data, which lead to powerful new insights,” said , Ph.D., dean of FAU’s College of Engineering and Computer Science. “This significant grant from the National Science Foundation will enable our project team to develop an innovative and integrative curriculum that will provide our graduate students and the companies and institutions they will serve with a leading-edge to take them to the top of their field or industry.”

The ֱresearch team is led by , Ph.D., principal investigator, a professor in the , and director of the NSF Industry/University Cooperative Research Center for Advanced Knowledge Enablement (CAKE), FAU’s College of Engineering and Computer Science.

“Data scientists are not just statisticians or machine learning experts; they also are authorities in the field or business where they are applying those skills,” said Furht. “Effective data scientists need to be able to work in interdisciplinary teams and to use data visualization and communication skills to communicate their findings to individuals not trained in data science. Our program will produce graduates with technical depth and understanding of data science technologies and applications.”

The project team includes , Ph.D., senior associate dean for research and chair, in FAU’s Schmidt College of Medicine, and an expert on genomic analysis; , Ed.D., Christine E. Lynn Eminent Scholar and Professor, FAU’s Christine E. Lynn College of Nursing, and an expert on nursing management and memory disorders; , Ph.D., Motorola Professor in the Department of Computer and Electrical Engineering and Computer Science, and an expert on medical applications of big data analytics; , Ph.D., an associate professor of psychology, FAU’s Charles E. Schmidt College of Science, and an expert on deep learning and brain behavior; , Ph.D., a professor in the Department of Computer and Electrical Engineering and Computer Science, and an expert on deep networks and its applications; Oge Marques, Ph.D., an expert on data science and AI in medical applications; , Ph.D., an assistant professor in the , and an expert on data analytics in the Internet of Things (IoT) and transportation, and a fellow of FAU’s Institute for Sensing and Embedded Networks Systems Engineering (I-SENSE); , Ph.D., associate chair and professor, Department of Computer and Electrical Engineering and Computer Science, and an expert on software optimization; and Camellia Sanford-Dolly, an education and evaluation expert.

Thirty faculty members from five ֱcolleges and 10 departments will participate in the program. 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. A total of 45 trainees will be funded by the program: 30 Ph.D. students and 15 master’s students. In addition, the researchers expect to include in the cohort 10 to 12 Ph.D. students and 12 to 15 master’s students each year who will be supported by other grants and related departments.

“While data science technologies and applications have evolved significantly over the last several years, it is clear that current graduate training in data science does not sufficiently prepare students for future challenges as researchers and practitioners in data science and its applications,” said , Ph.D., FAU’s vice president for . “With this grant from the National Science Foundation, our interdisciplinary team at ֱ will leverage their extensive expertise and talents to provide a unique and comprehensive training opportunity for the next generation of data scientists.”  

The convergent research themes will focus on three data science and analytics areas: medical and health care applications, industry applications, and data science and artificial intelligence (AI) technologies. Each course will be developed by at least two faculty members from two different disciplines. Integrated research and training and multiple testbeds for different application domains will be developed in FAU’s new NSF-funded Artificial Intelligence and Deep Learning 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 CAKE at FAU.

-FAU-