Demo Data from EDBT 2026 / reviewers in the wild / expert
Sriya Kasumarthi
dblp:390/0451
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Human-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 · 50% Human-robot interaction · 50% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Immersive interaction
augmented reality |
0.9 | 1 | 2025 | Investigating Encoding and Perspective for Augmented Reality Motion Guidance · ISMAR 2025 |
Human-robot interaction › physical human-robot interaction
motion guidance |
0.9 | 1 | 2025 | Investigating Encoding and Perspective for Augmented Reality Motion Guidance · ISMAR 2025 |
Visualization and visual analytics
visual encoding |
0.3 | 1 | 2025 | Investigating Encoding and Perspective for Augmented Reality Motion Guidance · ISMAR 2025 |
Methods — techniques the papers use, named apart from their topics
user study · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Investigating Encoding and Perspective for Augmented Reality Motion GuidanceabstractAugmented reality (AR) offers promising opportunities to support movement-based activities, such as personal training or physical therapy, with real-time, spatially-situated visual cues. While many approaches leverage AR to guide motion, existing design guidelines focus on simple, upper-body movements within the user's field of view. We lack evidence-based design recommendations for guiding more diverse scenarios involving movements with varying levels of visibility and direction. We conducted an experiment to investigate how different visual encodings and perspectives affect motion guidance performance and usability, using three exercises that varied in visibility and planes of motion. Our findings reveal significant differences in preference and performance across designs. Notably, the best perspective varied depending on motion visibility and showing more information about the overall motion did not necessarily improve motion execution. We provide empirically-grounded guidelines for designing immersive, interactive visualizations for motion guidance to support more effective AR systems. Jade Kandel, Sriya Kasumarthi, Spiros Tsalikis, Chelsea Duppen, Daniel Szafir, Michael Lewek, Henry Fuchs, Danielle Albers Szafir |
ISMAR | 2 |