solving problems in an


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Working to discover and inspire fundamentally new ways to measure, model, predict and visualize meaningful interactions
and interconnectivity of social, physical and technological systems

Home of the nation's first doctoral program in Network Science

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phd program

"Most dis­ci­plines, from physics to soci­ology and health sci­ences, are challenged by com­plex net­works. This new PhD pro­gram is not only about furthering the dis­ci­pline of net­work sci­ence, it is also about training experts who can enrich their respec­tive dis­ci­pline, helping their col­leagues to deal with the com­plex sys­tems they need to con­front. It is a pio­neering pro­gram that truly embodies inter­dis­ci­pli­nary thinking."

Albert-​​László Barabási

Director, CCNR

The PhD program in Network Science at Northeastern University is a new interdisciplinary program that provides technical tools and concepts for understanding the structure and dynamics of networks across diverse domains, such as human behavior, socio-technical infrastructures, and biological agents. 

interdisciplinary thinking

Network Science is deeply interdisciplinary, yet shares a common technical and conceptual core. Our PhD students develop expertise in these core concepts, and gain exposure to network science researchers across a wide range of fields, including computer science, information science, complexity, physics, sociology, communication, organizational behavior, political science, and epidemiology.

world-renowned faculty

Northeastern University is a world leader in Network Science, with prominent faculty in the field including Albert- László Barabási, Alessandro Vespignani, David Lazer, Tina Eliassi-Rad and numerous affiliated faculty, centers and labs with scores of researchers. A key element of the program involves careful mentoring from these faculty and immediate involvement in the cutting edge research taking place at the Institute. Formal concentrations of study integrate the student into Northeastern’s disciplinary domains, including physical sciences, social science, health science, or computer and information sciences. Our approach to interdisciplinary learning is to provide a core technical and theoretical foundation, after which the student is offered lab rotations and self-directed exploration of Network Science applications and mentorship.

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