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Sau-Lai Lee

dblp:43/4374 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2012
0000-0001-7158-3651ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 2 first-authorSystems, architecture and hardware · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-authorApplied, interdisciplinary, general and emerging 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
2 papers
Human-robot interaction · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
robot ethics
0.112011
Hitting a robot vs. hitting a human: is it the same? · HRI 2011
Human-robot interaction › cognitive human-robot interaction
mental models of robots
0.112005
Human Mental Models of Humanoid Robots · ICRA 2005
Human-robot interaction › human behavior modeling › social perception
social perception of robots
0.012011
Hitting a robot vs. hitting a human: is it the same? · HRI 2011
Human-robot interaction
user perception of robot
0.012005
Human Mental Models of Humanoid Robots · ICRA 2005

Methods — techniques the papers use, named apart from their topics

survey study · 0.1human-subject experiment · 0.1
YearPublicationVenuePosition
2012 Analysis of Qualities of Effective Teachers and Issues on Designing Educational Robots
abstract
This paper provides a theoretical analysis of the feasibility of developing a robot that could take the role of an effective teacher by examining qualities and roles of effective teachers in the classrooms.
Ilker Yengin, Sau-Lai Lee, Martin Saerbeck
ICCE2
2011 Hitting a robot vs. hitting a human: is it the same?
abstract
The present project aimed to study how people make moral judgment for human versus robot behaviors. Ten transgression scenarios were presented to the participants with either a human or a robot as the perpetrator or the victim. Results showed that most of the transgressions were perceived as less immoral when it was acted on a robot than on a human. Moral judgments for human behaviors were more intuitive and emotion based. Moral judgments for robot behaviors involve both intuition and cognitive reasoning. Possible psychological causes were discussed.
Sau-Lai Lee, Ivy Yee-man Lau
HRI1
2005 Human Mental Models of Humanoid Robots
abstract
Effective communication between a person and a robot may depend on whether there exists a common ground of understanding between the two. In two experiments modelled after human-human studies we examined how people form a mental model of a robot’s factual knowledge. Participants estimated the robot’s knowledge by extrapolating from their own knowledge and from information about the robot’s origin and language. These results suggest that designers of humanoid robots must attend not only to the social cues that robots emit but also to the information people use to create mental models of a robot.
Sau-Lai Lee, Sara B. Kiesler, Ivy Yee-man Lau, Chi-Yue Chiu
ICRA1