Demo Data from VLDB 2026 / reviewers in the wild / expert
Zhuoyi Zhang
dblp:273/5866
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2026
0009-0001-0308-6861ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2 · 2 since 2021Artificial intelligence and machine learning · 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
2 papers |
Human-AI interaction · 39% Personal fabrication and tangible interfaces · 29% Learning and educational technologies · 12% |
Topics — the 3 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Personal fabrication and tangible interfaces › digital fabrication
inflatable fabrication |
0.8 | 1 | 2024 | SnapInflatables: Designing Inflatables with Snap-through Instability for Responsive Interaction · CHI 2024 |
Learning and educational technologies › informal learning
family co-learning |
0.3 | 1 | 2026 | DOLLama: Fostering Family Anti-Bullying Learning through AI-Augmented, Toy-Mediated Educational Drama · CHI 2026 |
Haptics and multimodal interaction
haptic feedback |
0.2 | 1 | 2024 | SnapInflatables: Designing Inflatables with Snap-through Instability for Responsive Interaction · CHI 2024 |
Methods — techniques the papers use, named apart from their topics
projection-augmented interaction · 1.0generative AI · 1.0inflation simulation · 0.8heat-sealing · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | DOLLama: Fostering Family Anti-Bullying Learning through AI-Augmented, Toy-Mediated Educational DramaabstractEducational drama is a proven method for anti-bullying education, but its traditional reliance on teachers and peers limits its accessibility to children and families outside of school. HCI has rarely explored how to augment this practice with AI-infused, interactive role-playing or how to involve parents in the process. We introduce DOLLama, an AI-powered projection-augmented interactive system that transforms children’s toys and family-created stories into gamified anti-bullying vignettes. A study with 20 families demonstrated how DOLLama facilitated children’s and parents’ learning. Children used their toys to enact the roles of the one being bullied and bystanders, developing empathy and practicing coping strategies in co-performance with AI-controlled toy characters. By observing this play, parents gained new insights into their child’s strengths and challenges and identified their own knowledge gaps. Based on these findings, we derive HCI design implications for AI-enhanced, toy-mediated educational drama that supports anti-bullying education for children and their families. Di Liu 0025, Zhuoyi Zhang, Yufei Hu, Keming Jiao, Xueliang Li 0012, Pengcheng An |
CHI | 3 |
| 2024 | SnapInflatables: Designing Inflatables with Snap-through Instability for Responsive InteractionabstractSnap-through instability, like the rapid closure of the Venus flytrap, is gaining attention in robotics and HCI. It offers rapid shape reconfiguration, self-sensing, actuation, and enhanced haptic feedback. However, conventional snap-through structures face limitations in fabrication efficiency, scale, and tunability. We introduce SnapInflatables, enabling safe, multi-scale interaction with adjustable sensitivity and force reactions, utilizing the snap-through instability of inflatables. We designed six types of heat-sealing structures enabling versatile snap-through passive motion of inflatables with diverse reaction and trigger directions. A block structure enables ultra-sensitive states for rapid energy release and force amplification. The motion range is facilitated by geometry parameters, while force feedback properties are tunable through internal pressure settings. Based on experiments, we developed a design tool for creating desired inflatable snap-through shapes and motions, offering previews and inflation simulations. Example applications, including a self-locking medical stretcher, interactive animals, a bounce button, and a large-scale light demonstrate enhanced passive interaction with inflatables. Yue Yang 0005, Zhuoyi Zhang, Yanchen Shen, Kuangqi Zhu, Junzhe Ji, Yongbo Ni, Jiayi Wu 0008, Qi Wang 0075, Jiang Wu 0019, Lingyun Sun, Ye Tao 0001, Guanyun Wang |
CHI | 5 |
| 2021 | Siamese network for object tracking with multi-granularity appearance representations
Zhuoyi Zhang, Yifeng Zhang 0001, Xu Cheng 0003, Guojun Lu |
Pattern Recognit. | 1 |