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The Center for Data Science & Technology (CDST) at School of Communication & Information (SC&I) provides a multidisciplinary platform for advancements in research, development, and education pertaining to data science and related topics. The focus of this center is on understanding data in the context in which it is generated and used. In addition, scholars affiliated with this center are actively applying data science to studying and solving problems in various application domains including health, finance, networks, education, and policy, and creating new knowledge by turning data into insights.

Depth of Context Understanding


We have world-renowned faculty members who specialize in Data Science in the context of communication, information sciences, and media research. We are interested analyzing pertinent data, and extracting insightful information grounded in context. For instance, in addition to analyzing electronic health records, we are interested in investigating how those patients perceive and seek health- related information and support from both professionals and peers.

Diversity of Learning Opportunities


With a special emphasis on Computational Social Science, we have a unique environment that provides our faculty and students with a breadth of fields involving the social, technical and the socio-technical aspects of Data Science. Our faculty have expertise and support covering topics ranging from database management, to ethics of data archiving, to social informatics, and social media/networks analysis. We employ and teach methods that involve data analytics, text mining, machine learning, and computational modeling.

Strong Industry
Connections


The unique location of Rutgers within the New York metropolitan area allows our faculty and students to develop strong connections with multiple technical, business-oriented, and social institutions that are interested in hiring Data Science professionals. Multiple industry partners routinely visit our campus to advise students on career and growth opportunities. These industry contacts and collaborators are not only looking for technical capabilities or business analytics skills; they are also looking for a deeper understanding like the one we bring to Data Science problems that involve studying people and organizations in context.