About the Institute

NetSI brings together labs, research teams, and doctoral students from diverse disciplinary backgrounds joined by our shared interest in understanding the patterns and dynamics of connectivity underlying behaviors of complex systems.  Both our collaborative research and educational strategies are motivated by a desire to inspire and contribute to a growing community dedicated to fundamentally changing the way society understands and interacts with our networked world.

Collectively our Institute research explores large scale data sets that enable us to develop heavily mechanistic and statistically rigorous models to measure and model network properties and interdependencies of physical, social, informational and technical systems. Using visualizations and forecasting models, we actively engage government, industry and other decision-making partners to inform and advise how to design or restore the network to reach its desired outcome.

The Network Science Institute (NetSI) is a multi-disciplinary research community supporting innovative research and training in network science. Located next to the Prudential Center, a short walk from the main campus of Northeastern University, NetSI is a collection of labs, research teams, and doctoral students in a shared workspace, representing diverse academic departments, including physics, political science, communication, computer science, health sciences, and business.  We have active speaker series, journal clubs and working groups, a shared computing infrastructure, and a set of intensive network science graduate courses. From the nexus of cross-disciplinary exchanges, our Institute is dedicated to creating synergy across research areas, with projects that integrate models, theories and problem-solving approaches from diverse perspectives and applications with the shared goal to understand systems by discovering the underlying principles, properties and purpose of their connectivity.

Research conducted at the Institute explores diverse network phenomena such as diffusion and spreading, control and resilience and coordination and collective behaviors. In our fundamental mathematical and theoretical research, we explore geometry of networks, and formalized representations of multi-dimensional networks. Current research projects include topics such as disease spread through populations, the role of cellular and sub-cellular connections in biological functionhow social movements form and mobilize, the evolution of knowledge and emergence of scientific discoveriesdesign and recovery of socio-technical systems, and how groups deliberate, learn and reach consensus.

With the goal of training a new generation of scholars, the Institute has developed the first PhD program in Network Science in the U.S.  Our curriculum includes six courses designed to provide the set of core foundational skills to become highly competent modelers and agile thinkers in this field: Introduction to Network Science; Dynamical Systems; Network Data; Social Networks; Bayesian Statistics; and Network Economics. We are also committed to developing teaching modules for k-12 students, with the vision of providing tools and a framework for educators for the identification and exploration of disciplinary intersections across required curriculum content. Together, we hope these efforts will help train new science scholars with the computational skills and disciplinary depth to become visionary thought leaders, as well as support the efforts to use science of learning and information to improve the depth and quality of education.

Working to discover and inspire fundamentally new ways to measure, model, predict and visualize meaningful interactions and interconnectivity of social, physical and technological systems; explore their universality and predictability;
and inform intervention strategies to improve health and security of human populations.

What is network science?

Each year, the Department of Defense (DoD) identifies important areas of research that are most likely to transform future technology capabilities over the next 20 years.  The topic of the most recent meeting was Network Science, for which the Network Science Institute’s co-founder, Albert-Laszlo Barabási and the Institute’s Director, Alessandro Vespignani, were designated as Chairs.

The Future Directions of Network Science Workshop was held in September, 2016 in Arlington, VA. Twenty-five of the world’s top network science researchers and ten government scientists gathered together, representing dozens of Universities, agencies, and scientific disciplines. For two days, we engaged in energetic dialogue about the promises and challenges of this emerging field, and worked together to map the trajectory of network science research over the next 5, 10, and 20 year horizon.  The report here summarizes the major insights and themes that resulted from the meeting.
Our distinguished Speaker Series brings eminent global thought leaders from across basic and applied research, in physics, biology, computer science, mathematics, economics, behavioral and social sciences, to inspire and inform researchers in the development of the next generation of scientific technologies and discoveries.

As the world becomes more globally connected, it is increasingly defined by its interdependencies. The emerging field of network science provides a powerful set of tools and conceptual framework for evaluating and modeling complex systems. Network science draws on theories and methods from physical, information and social sciences to describe, prescribe and predict dynamics and behavior of networks. Despite their diversity, the processes and behaviors of different kinds of networks share many common organizing principles and thus can be studied with similar approaches. Network science research is characterized by relationally driven inquires to understand:  

how networks form, grow, transform, dissolve, evolve, learn, coordinate, converge and behave collectively

how networks facilitate the flow and the spread of information, disease, behaviors, and resources

how information can transform a network through which it travels (and vice versa)

what it means to be a resilient, healthy or optimized network

what control mechanisms govern networks, and at what time and place can we intervene to rehabilitate or disrupt a network

Network approaches require sophisticated mathematical techniques, highly complex and relational data sets, and the continued development of new theories to explore properties and mechanisms of complexsystems.