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Research

We forecast social, health, and infrastructure outcomes by modeling complex scenarios

How can we best fight infectious disease outbreaks? When will a social media protest become a civil crisis? We investigate large-scale biological, social, and technological systems at play in the world. By simulating scenarios of unfolding situations, we provide insights to help decision-makers refine science-based responses. In the process, we produce high-tech tools and foundational knowledge that advance the science of biocomplexity.

Areas of Focus

We apply our computational modeling tools and combined expertise to tackle a broad swath of issues affecting human life – from improving disaster resiliency in city infrastructures to identifying previously unknown organisms in our environments and bodies.

We develop tools to distill vast medical and ecological data and share them with research scientists, healthcare professionals and policymakers.

By computing predictive models, we provide public-health policymakers with data and analysis to identify and respond to epidemics.

We explore the information content in structured sequence data to reveal how changes in one influence the time evolution of the other. This contributes unique insights into viral dynamics at the host population level.

We investigate the structure of large bio-networks such as long noncoding RNA molecules. This contributes to the understanding of cancer development.

We study the abstraction to shape of a biological system - using it as a mathematical language to measure its complexity of interaction and provide ways of decomposing it into more fundamental blocks. This contributes to the understanding of ncRNA and structure switching.

Tackling community issues such as economic mobility and improving access to food, housing, and jobs to advance community health and well-being.

Improving the well-being of citizens across the nation through the health of our national systems from food to defense to technology.

Assessing the use of non-survey data flows to supplement or enhance current development of Official Statistics.

Research Spotlight

Modeling for COVID-19

We've modeled several epidemics in the past 20 years, including H1N1 and Ebola. Today, collaborating with researchers from across the Institute and the University of Virginia, we're modeling scenarios to help governments and the global research community understand and mitigate the spread of COVID-19.

Student Opportunities

Computing for Global Challenges Program

From human health to infrastructure, our world is facing enormous threats. To understand them, we need and use data. This undergraduate program is a training ground for the next generation of data-driven researchers. Working in teams with peers and scientists from the Institute's Network Systems Science and Advanced Computing division, students learn a new way to address real-world issues while working on critical research projects.

All Projects

Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C) is a Smart Health sensing system created by engineers and clinicians at the University of Virginia designed to monitor, predict and manage cancer pain in the home setting. Managing cancer pain at home can be stressful and challenging, but BESI-C offers a user-friendly and non-invasive solution.
Past Project
We are studying the spread of invasive plants in the Chitwan Annapurna Landscape (CHAL) of Nepal, which is part of a biodiversity hotspot. This problem of invasive species is an impediment to the achievement of multiple sustainable development goals drafted by the United Nations. CHAL has a rich diversity of flora and fauna, which is unfortunately threatened by the combined effects of climate change and increased human activities.
The Broad One Health Endectocide-based Malaria Intervention in Africa (BOHEMIA) project aims to reduce malaria transmission by administering ivermectin to humans and livestock. Ivermectin is an endectocide drug with an excellent safety profile that can kill ecto- and endoparasites, as well as mosquitoes that feed on treated humans or animals.

All Publications

Network Systems Science and Advanced Computing
Laubenbacher, R; Adler, F; An, G; Castiglione, F; Eubank S; Fonseca, L.; Glazier, J.; Helikar, T.; Jett-Tilton, M.; Kirschner, D.; Macklin, P.; Mehrad, B.; Moore, B.; Pasour, V.; Shmulevich, I.; Smith, A.; Voigt, I.; Yankeelov, T.; Ziemssen, T. . npj Systems Biology and Applications. 2024; 10
Network Systems Science and Advanced Computing