EDBT 2026 Demo / reviewers in the wild / expert
Zheyuan Kuang
dblp:361/2333
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0009-0184-6159ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 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.
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 87% Wearable and physiological sensing · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Immersive interaction
emotion elicitation |
1.0 | 1 | 2026 | Understanding the Effects of Interaction on Emotional Experiences in VR · CHI 2026 |
Immersive interaction
virtual reality |
1.0 | 1 | 2026 | Understanding the Effects of Interaction on Emotional Experiences in VR · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
within-subject study · 1.0multimodal physiological measurement · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Understanding the Effects of Interaction on Emotional Experiences in VRabstractVirtual reality has been effectively used for eliciting emotions, yet most research focuses on the intensity of affective responses rather than on how interaction influences those experiences. To address this gap, we advance a validated VR emotion-elicitation dataset through two key extensions. First, we add a new high-arousal, high-valence scene and validate its effectiveness in a within-subject study (N=24). Second, we incorporate interactive elements into each scene, creating both interactive and non-interactive versions to examine the impact of interaction on emotional responses. We evaluate interaction through a multimodal approach combining subjective ratings and physiological signals to capture both conscious and unconscious affective responses. Our evaluation study (N=84) shows that interaction not only amplifies emotions but modulates them in context, supporting coping in negative scenes and enhancing enjoyment in positive scenes. These findings highlight the potential of scene-tailored interaction for different applications, where regulating emotions is as important as eliciting them. Zheyuan Kuang, Tinghui Li 0001, Weiwei Jiang 0001, Sven Mayer, Flora D. Salim, Benjamin Tag, Anusha Withana, Zhanna Sarsenbayeva |
CHI | 1 |