EDBT 2026 Demo / reviewers in the wild / expert
Boris Bedic
dblp:314/9432
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
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% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics
high-dimensional data visualization |
0.7 | 1 | 2023 | Interactive Visual Analysis of Structure-borne Noise Data · IEEE Trans. Vis. Comput. Graph. 2023 |
Visualization and visual analytics › visual analytics
interactive visual analysis |
0.7 | 1 | 2023 | Interactive Visual Analysis of Structure-borne Noise Data · IEEE Trans. Vis. Comput. Graph. 2023 |
Visualization and visual analytics
visual analytics |
0.7 | 1 | 2023 | Interactive Visual Analysis of Structure-borne Noise Data · IEEE Trans. Vis. Comput. Graph. 2023 |
Methods — techniques the papers use, named apart from their topics
split boxplots · 0.7linked views · 0.7drill-down view · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Interactive Visual Analysis of Structure-borne Noise DataabstractNumerical simulation has become omnipresent in the automotive domain, posing new challenges such as high-dimensional parameter spaces and large as well as incomplete and multi-faceted data. In this design study, we show how interactive visual exploration and analysis of high-dimensional, spectral data from noise simulation can facilitate design improvements in the context of conflicting criteria. Here, we focus on structure-borne noise, i.e., noise from vibrating mechanical parts. Detecting problematic noise sources early in the design and production process is essential for reducing a product's development costs and its time to market. In a close collaboration of visualization and automotive engineering, we designed a new, interactive approach to quickly identify and analyze critical noise sources, also contributing to an improved understanding of the analyzed system. Several carefully designed, interactive linked views enable the exploration of noises, vibrations, and harshness at multiple levels of detail, both in the frequency and spatial domain. This enables swift and smooth changes of perspective; selections in the frequency domain are immediately reflected in the spatial domain, and vice versa. Noise sources are quickly identified and shown in the context of their neighborhood, both in the frequency and spatial domain. We propose a novel drill-down view, especially tailored to noise data analysis. Split boxplots and synchronized 3D geometry views support comparison tasks. With this solution, engineers iterate over design optimizations much faster, while maintaining a good overview at each iteration. We evaluated the new approach in the automotive industry, studying noise simulation data for an internal combustion engine. Rainer Splechtna, Denis Gracanin, Goran Todorovic, Stanislav Goja, Boris Bedic, Helwig Hauser, Kresimir Matkovic |
IEEE Trans. Vis. Comput. Graph. | 5 |