Network Systems Science and Advanced Computing

Projects

All Projects

BV-BRC is the Bacterial and Viral Bioinformatic Resource Center in this program, providing access to comprehensive datasets including genomics, structures, functions, and more.  BV-BRC also provides computational tools to quickly analyze data and make predictions using artificial intelligence techniques. The BV-BRC platform enables researchers to fully maximize the value of data related to pathogens.
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Population Health Informatics,Systems Biology and Bioinformatics
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.
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Resilient Societies and Interdependent Infrastructures
This project aims to reduce malaria transmission by administering ivermectin to humans and livestock. Ivermectin is an endectocide, a drug that can kill ecto- and endoparasites, as well as mosquitoes that feed on treated humans or animals. The overall goal of the project is to conduct randomized control trials through mass drug administration of ivermectin (iMDA) in humans and animals in Tanzania and Mozambique.
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Population Health Informatics
The major goal of this project is to design, build, verify, and deploy an open-access general-purpose CI for network science, which we call net.science.
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Resilient Societies and Interdependent Infrastructures
The overall goal of this project is to develop methods for prediction of incidence rates and patient risk to HAIs and evaluate interventions to control their spread. The mechanisms of HAI transmission and antimicrobial resistance are very complex, and the available data are sparse and noisy. Therefore, risk prediction and evaluation of interventions cannot be done by simple statistical models restricted to one hospital.
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Population Health Informatics
This project brings together a systems science approach, combines agent-based stochastic epidemic models, and techniques from machine learning, high performance computing, data mining, and spatial statistics, along with novel public and private datasets on immunization and incidence, to develop a novel methodology for identifying critical undervaccinated clusters.
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Population Health Informatics
This project has led to the development of a broad class of highly scalable libraries for problems in multiple areas, including network science, computer vision, bioinformatics and climate science. Team members have contributed by developing scalable algorithms for network generation and subgraph detection, which have been applied to problems in public health.
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Population Health Informatics,Resilient Societies and Interdependent Infrastructures,Social, Cognitive, and Behavioral Science
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Resilient Societies and Interdependent Infrastructures
This Expeditions project will enable novel implementations of global infectious disease computational epidemiology by advancing computational foundations, engineering principles, theoretical understanding, and novel technologies.
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Population Health Informatics
This project provides a methodology and theory development that spans the information ecology, dis/mis-information, and human risk behavior in the context of COVID-19.  The primary methods use computational models of psychological and cognitive processes, dis/mis-information propagation detection, natural language processing techniques and agent-based modeling to provide a forecasting tool for exploring what-if scenarios and situational assessment.
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Social, Cognitive, and Behavioral Science