Network Systems Science and Advanced Computing

The Network Systems Science and Advanced Computing Division uses information science to create solutions for complex societal problems. Our simulation systems are critical to the success of detecting new threats, natural and man-made, and planning strategic responses.
We have a number of large, ongoing projects, including:

Developing middleware to support Network Science. This middleware allows Network Scientists to access an exceptional computing and analysis environment for research, training and education.

Disaster Response

Designing effective responses to global natural and human-influenced crises requires an interdisciplinary approach, synthesizing timely and reliable data, understanding of human behaviors, analytical capabilities, technology and computing power, realistic models and an agile team to analyze and mitigate the social and economic impact on societies. The NSSAC Laboratory uses modeling and simulation capabilities to provide effective response and planning during times of national disasters. These strategies bolster national security, increase the ability to design resilient cities, and increase overall societal security and well-being.

DOE SunShot

This project is focused on understanding the social and behavioral factors that contribute to the adoption of rooftop solar panels in rural regions. We work with many partners, including the National Rural Electric Cooperative Association, to identify the unique challenges faces by rural communities, especially in Virginia, in adopting solar.

Friend or Foe

The Friend or Foe program aims to develop biosurveillance technology that can detect bacterial pathogens as, or even before, they threaten the military and homeland. The goal of the program is to quickly determine whether an unknown bacterium is harmless or virulent by directly identifying pathogenic behavior, avoiding conventional strategies that rely on known biomarkers. The Biocomplexity Institute is partnering with Texas A&M University and Argonne National Labs in this endeavor.


This project uses machine learning to apply the world's knowledge about nucleotide sequences to determine whether synthesizing short sequences of DNA could pose a threat.


This group uses mathematical and computational methods to explore the effects of human interactions on influenza transmission and dynamics and response strategies. The tools and methods developed by the modelers have been used by a variety of stakeholders to better understand emerging infectious diseases in general.


PATRIC is one of four Bioinformatics Resource Centers for Infectious Diseases. It supports the biomedical research community's work by integrating pathogen information, data, and analysis as it relates to bacterial infectious diseases.

Public Health Policy Planning

In support of federal agencies (DoD, NIH, etc.) during the 2014 Ebola outbreak in West Africa, we provided analytical support to public health officials through better prediction of the spatial and temporal spread of the epidemic, better placement of medical equipment and hospital staff, and logistical support to share data, visualization resources, scalable tools and decision support systems among the public health community.


This program develops simulation methods that integrate sociological, cognitive and neural theory into at-scale, data-heavy social simulation using a newly developed agent-based modeling platform (the MATRIX). By virtue of the platform, this work also has implications for the foundations of sociological, cognitive and neural theory.

Social Pathways

Research which transforms social behavior into mathematical models of infectious disease vectors to provide a better understanding of how policies will work once implemented. The goal of this research is to understand feedback processes between health behaviors, disease evolution and interventions in order to improve public health policies.