Demo Data from SIGIR 2026 / reviewers in the wild / expert
Shira Bauman
dblp:159/0573
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2Artificial intelligence and machine learning · 1
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 |
Human-robot interaction · 100% | |
| Artificial intelligence
1 paper |
Motion planning and robot control · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
human-robot collaboration |
0.2 | 1 | 2015 | Effects of Robot Motion on Human-Robot Collaboration · HRI 2015 |
Human-robot interaction › nonverbal communication
legible robot motion |
0.2 | 1 | 2015 | Effects of Robot Motion on Human-Robot Collaboration · HRI 2015 |
Methods — techniques the papers use, named apart from their topics
user study · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Robotic experience companionship in music listening and video watching
Guy Hoffman, Shira Bauman, Keinan Vanunu |
Pers. Ubiquitous Comput. | 2 |
| 2015 | Effects of Robot Motion on Human-Robot CollaborationabstractMost motion in robotics is purely functional, planned to achieve the goal and avoid collisions. Such motion is great in isolation, but collaboration affords a human who is watching the motion and making inferences about it, trying to coordinate with the robot to achieve the task. This paper analyzes the benefit of planning motion that explicitly enables the collaborator's inferences on the success of physical collaboration, as measured by both objective and subjective metrics. Results suggest that legible motion, planned to clearly express the robot's intent, leads to more fluent collaborations than predictable motion, planned to match the collaborator's expectations. Furthermore, purely functional motion can harm coordination, which negatively affects both task efficiency, as well as the participants' perception of the collaboration. Anca D. Dragan, Shira Bauman, Jodi Forlizzi, Siddhartha S. Srinivasa |
HRI | 2 |