Demo Data from EDBT 2026 / reviewers in the wild / expert
Haonan Yao
dblp:221/7768
· DBLP profile ↗
3ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0003-1735-6281ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1Human-computer interaction and ubiquitous computing · 1 · 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 · 100% | |
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 67% Visualization and visual analytics · 33% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality
mixed reality |
0.2 | 1 | 2024 | Data Cubes in Hand: A Design Space of Tangible Cubes for Visualizing 3D Spatio-Temporal Data in Mixed Reality · CHI 2024 |
Virtual and augmented reality › immersive interaction
tangible interaction |
0.2 | 1 | 2024 | Data Cubes in Hand: A Design Space of Tangible Cubes for Visualizing 3D Spatio-Temporal Data in Mixed Reality · CHI 2024 |
Methods — techniques the papers use, named apart from their topics
workshop study · 1.5prototype evaluation · 1.5design space · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Data Cubes in Hand: A Design Space of Tangible Cubes for Visualizing 3D Spatio-Temporal Data in Mixed RealityabstractTangible interfaces in mixed reality (MR) environments allow for intuitive data interactions. Tangible cubes, with their rich interaction affordances, high maneuverability, and stable structure, are particularly well-suited for exploring multi-dimensional data types. However, the design potential of these cubes is underexplored. This study introduces a design space for tangible cubes in MR, focusing on interaction space, visualization space, sizes, and multiplicity. Using spatio-temporal data, we explored the interaction affordances of these cubes in a workshop (N=24). We identified unique interactions like rotating, tapping, and stacking, which are linked to augmented reality (AR) visualization commands. Integrating user-identified interactions, we created a design space for tangible-cube interactions and visualization. A prototype visualizing global health spending with small cubes was developed and evaluated, supporting both individual and combined cube manipulation. This research enhances our grasp of tangible interaction in MR, offering insights for future design and application in diverse data contexts. Shuqi He, Haonan Yao, Luyan Jiang, Yue Li 0023, Hai-Ning Liang, Lingyun Yu 0001 |
CHI | 2 |
| 2022 | A residual convolutional neural network based approach for real-time path planning
Yang Liu 0287, Zheng Zheng 0001, Fangyun Qin, Xiao-Yi Zhang 0005, Haonan Yao |
Knowl. Based Syst. | 5 |
| 2019 | Designing blockchain-based applications a case study for imported product traceability
Xiwei Xu 0001, Qinghua Lu 0001, Yue Liu 0010, Liming Zhu 0001, Haonan Yao, Athanasios V. Vasilakos |
Future Gener. Comput. Syst. | 5 |