Demo Data from SIGIR 2026 / reviewers in the wild / expert
Kristyn Sommer
dblp:232/9877
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-1045-612XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2Systems, architecture and hardware · 1Human-computer interaction and ubiquitous computing · 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% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
child-robot interaction |
0.4 | 1 | 2019 | Children's Judgments of Anti-Social Behaviour Towards a Robot: Liking and Learning · HRI 2019 |
Human-robot interaction
moral judgment |
0.4 | 1 | 2019 | Children's Judgments of Anti-Social Behaviour Towards a Robot: Liking and Learning · HRI 2019 |
Human-robot interaction › robot ethics
robot abuse |
0.1 | 1 | 2019 | Children's Judgments of Anti-Social Behaviour Towards a Robot: Liking and Learning · HRI 2019 |
Methods — techniques the papers use, named apart from their topics
user study · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Children's Judgments of Anti-Social Behaviour Towards a Robot: Liking and LearningabstractChildren have been documented extending prosocial ideals and moral worth towards robots. However, there is also emerging evidence that children will behave violently towards robots. Given expectations that robots will soon become common fixtures in classrooms, and that children can behave violently towards robots, it is important that we identify how others might appraise the victims (robots) and perpetrators (children) of these scenarios. It is critical that we understand whether children will think it is okay to behave immorally towards a robot, or if they will be deterred by these acts of abuse. Additionally, we must determine how this will influence children's learning decisions. The proposed study aims to address these questions by creating a novel paradigm where children are asked to rate robots and humans who have been involved in a transgression, where the human behaves anti-socially towards the robot. This study will also aim to understand how these appraisals will influence childrens learning decisions in a forced choice, selective learning task. Rebecca Davidson, Kristyn Sommer, Mark Nielsen |
HRI | 2 |
| 2018 | Designing for Robust Movement in a Child-Friendly RobotabstractMotion is a critical aspect of communication, required to create natural interactions between humans and robots. Robots for the classroom pose several constraints on motion, which make them challenging to design, including maintaining the safety of the child and the robot, responding in a timely fashion, and creating motions that are expressive and not scary. In this paper we present the mechanical design of a social robot and demonstrate that it is capable of safe motion within the proximity of children through analysis and empirical testing of the arms. The robot has a novel mechanical design for its two arms, which include torso-mounted, back-drivable, torque-limited stepper motors. The results suggest that our design succeeds at increasing safety levels while enabling the use of socially acceptable speeds of motion during the interaction. This study implies that the design of robotic agents for social interaction with children should consider the design of mechanical features that enable safe contact between the human and the robot while not limiting the robot to slow motions that would impair the timing of the interaction. Jonathon Taufatofua, Scott Heath, Carlos Andres Ramirez-Brinez, Kristyn Sommer, Gautier Durantin, Wilson Kong, Janet Wiles, Pauline Pounds |
IROS | 4 |