EDBT 2026 Demo / reviewers in the wild / expert
Aditya Bagaria
dblp:383/8480
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0009-8068-6623ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-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 |
Wearable and physiological sensing · 44% Ubiquitous computing and smart environments · 44% Interaction techniques and input · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Ubiquitous computing and smart environments › smart home
smart home interaction |
0.8 | 1 | 2024 | IRIS: Wireless ring for vision-based smart home interaction · UIST 2024 |
Wearable and physiological sensing › smart wearable
smart ring |
0.8 | 1 | 2024 | IRIS: Wireless ring for vision-based smart home interaction · UIST 2024 |
Interaction techniques and input
gesture input |
0.2 | 1 | 2024 | IRIS: Wireless ring for vision-based smart home interaction · UIST 2024 |
Methods — techniques the papers use, named apart from their topics
scene semantics · 0.8instance-level device recognition · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | IRIS: Wireless ring for vision-based smart home interactionabstractIntegrating cameras into wireless smart rings has been challenging due to size and power constraints. We introduce IRIS, the first wireless vision-enabled smart ring system for smart home interactions. Equipped with a camera, Bluetooth radio, inertial measurement unit (IMU), and an onboard battery, IRIS meets the small size, weight, and power (SWaP) requirements for ring devices. IRIS is context-aware, adapting its gesture set to the detected device, and can last for 16-24 hours on a single charge. IRIS leverages the scene semantics to achieve instance-level device recognition. In a study involving 23 participants, IRIS consistently outpaced voice commands, with a higher proportion of participants expressing a preference for IRIS over voice commands regarding toggling a device’s state, granular control, and social acceptability. Our work pushes the boundary of what is possible with ring form-factor devices, addressing system challenges and opening up novel interaction capabilities. Maruchi Kim, Antonio Glenn, Bandhav Veluri, Yunseo Lee, Eyoel Gebre, Aditya Bagaria, Shwetak N. Patel, Shyamnath Gollakota |
UIST | 6 |