Published On: Thu, Sep 10th, 2020

FAU Awarded $2.4M NSF Grant to Train Data Scientist

Researchers from Florida Atlantic University’s College of Engineering and Computer Science in collaboration with FAU’s Schmidt College of Medicine, Christine E. Lynn College of Nursing, and Charles E. Schmidt College of Science, 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.

A young woman is surrounded by monitors & their reflections displaying scrolling text & data.

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 Stella Batalama, 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.”

As Stella Batalama, Ph.D., emphasized, the field of big data and data science is evolving rapidly, demanding a workforce equipped with diverse skills to navigate and leverage the vast amounts of data available today. This demand isn’t confined to one industry; rather, it spans across various sectors, from healthcare to finance. In particular, the application of big data in finance has revolutionized the way financial institutions operate, enabling them to make more informed decisions, mitigate risks, and identify lucrative investment opportunities. By harnessing the power of big data analytics, financial institutions can analyze market trends, customer behavior, and economic indicators in real-time, allowing for more accurate predictions and strategic planning.

The FAU research team is led by Borko Furht, Ph.D., principal investigator, a professor in the Department of Computer and Electrical Engineering and Computer Science, 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 Janet Robishaw, Ph.D., senior associate dean for research and chair, Department of Biomedical Science in FAU’s Schmidt College of Medicine, and an expert on genomic analysis; Ruth Tappen, 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; Taghi Khoshgoftaar, 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; Elan Barenholtz, Ph.D., an associate professor of psychology, FAU’s Charles E. Schmidt College of Science, and an expert on deep learning and brain behavior; Xingquan (Hill) Zhu, 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; Jinwoo Jang, Ph.D., an assistant professor in the Department of Civil, Environmental and Geomatics Engineering, 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; Hari Kalva, 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 FAU 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 Daniel C. Flynn, Ph.D., FAU’s vice president for research. “With this grant from the National Science Foundation, our interdisciplinary team at Florida Atlantic University 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.

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