EDBT 2026 Demo / reviewers in the wild / expert
Shaun Kennedy
dblp:153/7555
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics › scientific visualization
computational steering |
0.2 | 1 | 2014 | VASA: Interactive Computational Steering of Large Asynchronous Simulation Pipelines for Societal Infrastructure · IEEE Trans. Vis. Comput. Graph. 2014 |
Visualization and visual analytics › visual analytics › visual analytics system
simulation-based visual analytics |
0.2 | 1 | 2014 | VASA: Interactive Computational Steering of Large Asynchronous Simulation Pipelines for Societal Infrastructure · IEEE Trans. Vis. Comput. Graph. 2014 |
Visualization and visual analytics
spatiotemporal visualization |
0.2 | 1 | 2014 | VASA: Interactive Computational Steering of Large Asynchronous Simulation Pipelines for Societal Infrastructure · IEEE Trans. Vis. Comput. Graph. 2014 |
Methods — techniques the papers use, named apart from their topics
visual analytics · 0.4distributed simulation · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | VASA: Interactive Computational Steering of Large Asynchronous Simulation Pipelines for Societal InfrastructureabstractWe present VASA, a visual analytics platform consisting of a desktop application, a component model, and a suite of distributed simulation components for modeling the impact of societal threats such as weather, food contamination, and traffic on critical infrastructure such as supply chains, road networks, and power grids. Each component encapsulates a high-fidelity simulation model that together form an asynchronous simulation pipeline: a system of systems of individual simulations with a common data and parameter exchange format. At the heart of VASA is the Workbench, a visual analytics application providing three distinct features: (1) low-fidelity approximations of the distributed simulation components using local simulation proxies to enable analysts to interactively configure a simulation run; (2) computational steering mechanisms to manage the execution of individual simulation components; and (3) spatiotemporal and interactive methods to explore the combined results of a simulation run. We showcase the utility of the platform using examples involving supply chains during a hurricane as well as food contamination in a fast food restaurant chain. Sungahn Ko, Jieqiong Zhao, Shehzad Afzal, Derek Xiaoyu Wang, Greg Abram, Niklas Elmqvist, Len Kne, David Van Riper, Kelly P. Gaither, Shaun Kennedy, William J. Tolone, William Ribarsky, David S. Ebert |
IEEE Trans. Vis. Comput. Graph. | 11 |