Demo Data from SIGIR 2026 / reviewers in the wild / expert
Jessica Lai
dblp:318/8055
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—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 |
Haptics and multimodal interaction · 100% | |
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality
virtual environment |
0.6 | 1 | 2022 | The Smell Engine: A system for artificial odor synthesis in virtual environments · VR 2022 |
Haptics and multimodal interaction › olfactory interfaces
olfactory display |
0.6 | 1 | 2022 | The Smell Engine: A system for artificial odor synthesis in virtual environments · VR 2022 |
Haptics and multimodal interaction › multimodal interaction
multimodal virtual environment |
0.2 | 1 | 2022 | The Smell Engine: A system for artificial odor synthesis in virtual environments · VR 2022 |
Methods — techniques the papers use, named apart from their topics
user study · 1.1diffusion model · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | The Smell Engine: A system for artificial odor synthesis in virtual environmentsabstractMimicking physical odor sensations virtually can present users with a real - time odor synthesis that approximates what users would smell in a virtual environment, e.g., as they walk around in virtual reality. To this end, we devise a Smell Engine that includes: (i) a Smell Composer framework that allows developers to configure odor sources in virtual space, (ii) a Smell Mixer that dynamically estimates the odor mix that the user would smell, based on diffusion models and relative odor source distances, and (iii) a Smell Controller that coordinates an olfactometer to physically present an approximation of the odor mix to the user’s mask from a set of odorants channeled through controllable flow valves. Through a three - part user study, we found that the Smell Engine can help measure a subject’s olfactory detection threshold and improve their ability to precisely localize odors in the virtual environment, as compared to existing trigger - based solutions. Alireza Bahremand, Mason Manetta, Jessica Lai, Byron Lahey, Christy Spackman, Brian H. Smith, Richard C. Gerkin, Robert LiKamWa |
VR | 3 |