Welcome to the Network Systems Science and Advanced Computing (NSSAC) collaboration page. We are a division of the Biocomplexity Institute and Initiative (BII) at the University of Virginia. We use advanced modeling techniques and simulations to study real world, cross-discipline problems. Our focus areas include Cognitive and Social Behaviors, Interdependent Infrastructures (like transportation and social media), Systems Biology, and Public Health (including epidemics and pandemics). This site provides access to materials relevant to current topics of interest in order to foster communication and collaboration. For more information about our research, please see our main webpage.
Check out our world class speakers on our YouTube channels: NSSAC, Global Pervasive Computational Epidemiology, PREPARE, Net.Science
We are proud to support the recently announced U.K.-U.S. prize challenges.
The challenge is focused on accelerating the adoption and development of privacy-enhancing technologies (PETs): Transforming financial crime prevention and boosting pandemic response capabilities through privacy-preserving federated learning.
Our team has generated the two synthetic population datasets provided in the pandemic response challenge. The first covers the population of the UK, and the second the population of the state of Virginia, USA. We used an outbreak simulation that created 63 days-worth of data, subsequently split into 56 days of training data and 7 days of test data.
Presented to Jiangzhuo Chen, Bryan Lewis, and Srini Venkatramanan as representatives of the Biocomplexity Institute’s COVID-19 Response Team for their service to the University, the Commonwealth of Virginia, and federal authorities during the pandemic, which continues today. Link
The team was selected as a finalist in the June 2021 Trinity Challenge for better protecting the world against health emergencies using data-driven research and analytics. 16 finalists were chosen out of 340 entries. Link
Presented to A Bhatele, J Yeom, N Jain, C Kuhlman, Y Livnat, K Bisset, L Kale, M Marathe for innovative use of HPC that led to scalable mapping of epidemic simulations on NERSC machines. Link
Presented to the team in the category of Data to Decisions for work on developing high performance computing solutions to support national disaster management. Link
Presented to the team for our work on simulating the entire US population in seconds versus an hour, helping to contain influenza outbreaks and optimizing placement of treatment centers for the Ebola outbreak. Link