Demo Data from SIGIR 2026 / reviewers in the wild / expert
Julio Medina
dblp:182/8835
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 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 |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality
immersive interaction |
0.3 | 1 | 2018 | Please Don't Puke: Early Detection of Severe Motion Sickness in VR · VR 2018 |
Virtual and augmented reality › immersive interaction
motion sickness |
0.3 | 1 | 2018 | Please Don't Puke: Early Detection of Severe Motion Sickness in VR · VR 2018 |
Immersive interaction › motion sickness
cybersickness detection |
0.3 | 1 | 2018 | Please Don't Puke: Early Detection of Severe Motion Sickness in VR · VR 2018 |
Virtual and augmented reality › locomotion
redirected walking |
0.1 | 1 | 2018 | Please Don't Puke: Early Detection of Severe Motion Sickness in VR · VR 2018 |
Methods — techniques the papers use, named apart from their topics
user study · 0.7fast motion sickness measure · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Please Don't Puke: Early Detection of Severe Motion Sickness in VRabstractMotion sickness is a potentially debilitating side effect experienced by certain users of virtual reality systems. Unexpected results from a user study on redirected walking suggest that there is a need to quickly identify participants who have an extremely low tolerance for virtual motion manipulations and remove them from the experience. In this poster, we investigate the use of a previously introduced “fast motion sickness” measure to identify potential outliers with heightened levels of sensitivity. This work demonstrates a promising experimental methodology and suggests possible shared characteristics among users in this group. Courtney Hutton, Shelby Ziccardi, Julio Medina, Evan A. Suma |
VR | 3 |