Henning S. Mortveit is an associate professor in the Network Systems Science and Advanced Computing division and in the Department of Engineering Systems and Environment. See faculty page.
How can we make a city and its physical infrastructures more resilient? How can existing infrastructures be modified to make a city more robust with respect to disasters? How do we reason about these questions in rigorous and efficient ways?
Modern cities are examples of highly complex systems that can be captured as massively interacting systems whose network components co-evolve with time. To capture these systems in a precise mathematical manner is a challenge that must address:
- modeling power
- ability to analytically analyze and validate mathematical models
- ability to efficiently implement models (construct simulation models) on current, high performance hardware
- scalability to accommodate simulation analysis needs in a timely manner
Mortveit’s research involves all these aspects and is rooted in the framework of Graph Dynamical Systems (GDS). This class of dynamical systems was introduced as a natural mathematical framework that permits precise modeling of massively interacting systems, and it addresses all the challenges above. His work covers both fundamental theory of GDS and their applications to system design, modeling, and analysis.
Part of his work covers software and system design for scalable, scientific computing. Ensuring scientifically reproducible computation for large scale simulation models is quite complex. Tracking all data sources, their provenance, their transformations to fit required input formats, the tracking of the tools and algorithms used to transform the data, as well as the simulation models that were used, give rise to many challenges. This work addresses this problem as well as efficient ways to add and combine simulation models for innovative and rapid modeling and analysis with integrated validation and data quality assessments.
Mortveit enjoys scientific visualization of spatial phenomena, in particular illustrations of dynamics of large, interaction-based systems involving synthetic information.
Keywords: Graph Dynamical Systems // Simulation Science // Stability Analysis (e.g., verification and validation, and sensitivity analysis)
Norwegian University of Science and Technology, Mathematics, Ph.D. 2000
Norwegian Institute of Technology, Mathematics, M.S. 1995
Los Alamos National Laboratory, Mathematics and Simulation, Postdoctoral Associate, 2000-2002
Los Alamos National Laboratory, Mathematics and Simulation, Staff member, 2002-2005
Virginia Tech, Department of Mathematics, and Biocomplexity Institute, Associate Professor, 2005-2018
The UVA Biocomplexity Institute has received a $1.44M award from the National Science Foundation for a Virtual Organization (VO) that will facilitate communication and collaboration among CISE scientists currently involved in pandemic research through the NSF RAPID program.
As the COVID-19 pandemic continues to escalate in the United States and in many locations around the world, countless questions remain about next steps for mitigation and response. How will various mitigation methods affect the spread? How will those change as the pandemic progresses or regresses?
Agricultural trade is crucial in delivering food to consumers worldwide. The benefits range from lower prices to greater variety in our food supply, and most importantly, the ability to reduce food insecurity across the globe. But, as international trade increases, so does the spread of invasive and destructive agricultural pests that can threaten food production and even destabilize our global food supply.
Modern food systems facilitate rapid dispersal of pests and pathogens through multiple pathways. The complexity of spread dynamics and data inadequacy make it challenging to model the phenomenon and also to prepare for emerging invasions.
Mortveit’s GDS Research Featured in Bulletin of Mathematical Biology