Data sciences is a rapidly advancing, interdisciplinary field that relies on techniques and theories drawn from machine learning, data mining, scalable data storage, and digital communication, as well as the disciplines of statistics, mathematics, and library sciences.
Research, educational, and professional training objectives are initially focused in three complementary areas: biomedical informatics, cybersecurity, and business analytics. The ethical use of large-scale data is an overarching theme that permeates all facets of work in these arenas.
Through this initiative, faculty and students will interact more broadly with producers of data, both on and off campus, and develop new methods to manage and interpret life sciences data, enterprise-scale business data, and data from other domains, as well as establish best practices for data analytics, integration, management, and security. This engagement can yield opportunity for the commercialization of technology - the process of taking ideas that emerge, giving them traction in the business community, and, thus, creating job opportunities. Further, as innovation drives commercialization, the reputation of the University is significantly enhanced. Commercialization of technology also may serve as a sustainable revenue source for further research growth.
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On April 14, Baylor University held its third annual Baylor Giving Day. For 24 hours, Baylor’s alumni, parents, faculty, staff, students and friends came together to give back and shine a light on the things they hold dear here. Baylor saw 3,942 people, foundations and organizations give to every academic unit and to all areas of the University, with a total of more than $1 million given to celebrate Baylor Giving Day.
