VLDB 2026 Research / reviewers in the wild / expert
Jingyi Zhang 0007
dblp:15/91-7
· DBLP profile ↗
4ranked-venue papers
3as first author
4since 2021 · last 2025
0009-0009-3432-3514ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-author · 3 since 2021Human-computer interaction and ubiquitous computing · 3 · 3 first-author · 3 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Do You See What I See? Bring Live Pedestrians into an Outdoor Collaborative Mixed Reality Experience
Jingyi Zhang 0007, Ziwen Lu, Changrui Zhu, Simon J. Julier, Anthony Steed |
UIST | 1 |
| 2025 | Single Actor Controlling Multiple Avatars for Social Virtual RealitiesabstractSocial virtual reality applications aim to provide immersive, interactive experiences in populated environments with virtual characters. However, developing characters capable of natural verbal and non-verbal interactions remains a significant challenge, particularly when it comes to managing complex and unexpected interactions with users. To address these issues, we present a system that supports full-body avatars with six-point tracking and a streamlined switch control procedure, allowing one actor to assume control of multiple virtual humans and interact seamlessly with the users. The system supports both verbal and non-verbal interactions. In an experiment, we showed that our system enhances the sense of co-presence, creating the feeling that multiple distinct, human-controlled characters are present in the scene. Jingyi Zhang 0007, Anthony Steed |
VR | 1 |
| 2023 | Supporting Co-Presence in Populated Virtual Environments by Actor Takeover of Animated CharactersabstractOnline social virtual worlds are now becoming widely available on consumer devices including virtual reality headsets. One goal of a virtual world could be to give a user an experience of a crowded environment with many virtual humans. However, gathering enough personnel to control the necessary number of avatars for creating a realistic scene is usually difficult. Additionally, current technology is not capable of fully simulating avatars with behaviours, especially when interaction with users is required. In this paper, we develop a system that enables an actor to take over control of one of a set of avatars. We built an immersive interface that allows an actor to select an avatar to take over and then segue into the currently playing animation. By allowing one person to take control of multiple avatars, we can enhance the plausibility of environments inhabited by simulated characters. In an experiment, we show that in a cafe scenario, one actor can take over the roles of a barista and two customers. Experiment participants reported experiencing the scene as if it were populated by more than one actor. This system and experiment demonstrate the feasibility of one actor controlling multiple avatars sequentially, thus enhancing users’ feelings of being in a populated environment. Jingyi Zhang 0007, Klara Brandstätter, Anthony Steed |
ISMAR | 1 |
| 2023 | Comparing Mixed Reality Agent Representations: Studies in the Lab and in the WildabstractMixed-reality systems provide a number of different ways of representing users to each other in collaborative scenarios. There is an obvious tension between using media such as video for remote users compared to representations as avatars. This paper includes two experiments (total n = 80) on user trust when exposed to two of three different user representations in an immersive virtual reality environment that also acts as a simulation of typical augmented reality simulations: full body video, head and shoulder video and an animated 3D model. These representations acted as advisors in a trivia quiz. By evaluating trust through advisor selection and self-report, we found only minor differences between representations, but a strong effect of perceived advisor expertise. Unlike prior work, we did not find the 3D model scored poorly on trust, perhaps as a result of greater congruence within an immersive context. Ben J. Congdon, Gun Woo (Warren) Park, Jingyi Zhang 0007, Anthony Steed |
VRST | 3 |