Demo Data from EDBT 2026 / reviewers in the wild / expert
Dmitry A. Karpeyev
dblp:162/2571
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2016
—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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational science and engineering
scientific visualization |
0.2 | 1 | 2016 | Extracting, Tracking, and Visualizing Magnetic Flux Vortices in 3D Complex-Valued Superconductor Simulation Data · IEEE Trans. Vis. Comput. Graph. 2016 |
Visualization and visual analytics
3d visualization |
0.1 | 1 | 2016 | Extracting, Tracking, and Visualizing Magnetic Flux Vortices in 3D Complex-Valued Superconductor Simulation Data · IEEE Trans. Vis. Comput. Graph. 2016 |
Methods — techniques the papers use, named apart from their topics
graph-based tracking · 0.5ginzburg-landau theory · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Extracting, Tracking, and Visualizing Magnetic Flux Vortices in 3D Complex-Valued Superconductor Simulation DataabstractWe propose a method for the vortex extraction and tracking of superconducting magnetic flux vortices for both structured and unstructured mesh data. In the Ginzburg-Landau theory, magnetic flux vortices are well-defined features in a complex-valued order parameter field, and their dynamics determine electromagnetic properties in type-II superconductors. Our method represents each vortex line (a 1D curve embedded in 3D space) as a connected graph extracted from the discretized field in both space and time. For a time-varying discrete dataset, our vortex extraction and tracking method is as accurate as the data discretization. We then apply 3D visualization and 2D event diagrams to the extraction and tracking results to help scientists understand vortex dynamics and macroscale superconductor behavior in greater detail than previously possible. Hanqi Guo 0001, Carolyn L. Phillips, Tom Peterka, Dmitry A. Karpeyev, Andreas Glatz |
IEEE Trans. Vis. Comput. Graph. | 4 |