Demo Data from EDBT 2026 / reviewers in the wild / expert
Steven Koepnick
dblp:32/6814
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-author
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 |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Collaborative and social computing · 77% Health and well-being technologies · 23% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality › virtual environment
immersive training |
0.1 | 1 | 2009 | Immersive Training for Two-Person Radiological Surveys · VR 2009 |
Virtual and augmented reality › immersive interaction
virtual reality training |
0.1 | 1 | 2009 | Immersive Training for Two-Person Radiological Surveys · VR 2009 |
Collaborative and social computing › social interaction
multi-user interaction |
0.1 | 1 | 2009 | Immersive Training for Two-Person Radiological Surveys · VR 2009 |
Methods — techniques the papers use, named apart from their topics
virtual simulation · 0.2multi-user interaction techniques · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | RIST: Radiological Immersive Survey Training for two simultaneous users
Steven Koepnick, Roger V. Hoang, Matthew R. Sgambati, Daniel S. Coming, Evan A. Suma, William R. Sherman |
Comput. Graph. | 1 |
| 2009 | Immersive Training for Two-Person Radiological SurveysabstractCivil Support Teams (CST) must be ready to respond to a variety of potential situations involving dangerous materials. For many of these materials, standard real-world training methods can be successfully employed. Training involving radiological agents, however, poses a greater challenge than for other agents due to a lack of materials that can suitably mimic the situation without the danger of the real material. To address the need of providing a good training system for learning how to behave when responding to a radiological threat, we have developed a CST immersive training system. Our system simulates a radiological threat in a virtual environment and allows users to practice surveying the threat using virtual representations of the world and necessary equipment. We developed novel multi-user interaction techniques to enable simultaneous training for two CST members. The 92ndCST tested the system and provided feedback throughout the development process. The team learned to use the system with little coaching, quickly learned to navigate and interact via wand controls, and ultimately performed a successful demonstration of a radiological survey using our system for their superior officers. Steven Koepnick, Derek Norpchen, William R. Sherman, Daniel S. Coming |
VR | 1 |