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Tomer Leivy

dblp:417/9702 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0009-1288-0934ORCID · corroborated

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

Artificial intelligence and machine learning · 2 · 2 since 2021Human-computer interaction and ubiquitous computing · 2 · 2 since 2021Applied, interdisciplinary, general and emerging 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
Human-robot interaction · 81% Health and well-being technologies · 19%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
social robot
1.012026
Emergency Department Waiting Experience: The Impact of an Attentive Robot · HRI 2026
Health and well-being technologies › healthcare work
emergency department
0.312026
Emergency Department Waiting Experience: The Impact of an Attentive Robot · HRI 2026
Human-robot interaction
healthcare robotics
0.312026
Emergency Department Waiting Experience: The Impact of an Attentive Robot · HRI 2026

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

field study · 1.0
YearPublicationVenuePosition
2026 Emergency Department Waiting Experience: The Impact of an Attentive Robot
abstract
It is well established that when people seek medical care for physical conditions, their affective state significantly impacts health and recovery. Despite this, patients’ emotional needs are often overlooked due to the prioritization of physical care and resource constraints. Robots’ social capabilities, especially robotic attentiveness, present an opportunity to address this gap and enhance patients’ experience in healthcare settings. While robots are already integrated into healthcare, they are largely leveraged for functional support, with limited attention to their potential role in addressing affective challenges. In this field study, we evaluated whether a simple attentive robot could improve the affective experience in the emergency department (ED) of a public general hospital. Participants’ waiting experience was compared across three conditions: (1) waiting next to an attentive robot; (2) waiting next to a non-attentive robot; and (3) waiting without a robot. Behavioral and self-report measures indicated that the attentive robotic behavior reduced the unpleasantness of the waiting experience. Our findings highlight the power of leveraging simple robotic attentiveness to support patients' affective state in stressful healthcare environments.
Yuval Rubin Kopelman, Dikla Dahan Shriki, Roy Cohen Elias, Tomer Leivy, Julian Waksberg, Mira Leybel, Jalal Ashkar, Mahmod Hamdan, Hadas Erel
HRI4
2025 A Matter of Height: The Impact of a Robotic Object on Human Compliance
abstract
Robots come in various forms and have different characteristics that may shape the interaction with them. In human-human interactions, height is a characteristic that shapes human dynamics, with taller people typically perceived as more persuasive. In this work, we aspired to evaluate if the same impact replicates in a human-robot interaction and specifically with a highly non-humanoid robotic object. The robot was designed with modules that could be easily added or removed, allowing us to change its height without altering other design features. To test the impact of the robot’s height, we evaluated participants’ compliance with its request to volunteer to perform a tedious task. In the experiment, participants performed a cognitive task on a computer, which was framed as the main experiment. When done, they were informed that the experiment was completed. While waiting to receive their credits, the robotic object, designed as a mobile robotic service table, entered the room, carrying a tablet that invited participants to complete a 300-question questionnaire voluntarily. We compared participants’ compliance in two conditions: A Short robot composed of two modules and 95cm in height and a Tall robot consisting of three modules and 132cm in height. Our findings revealed higher compliance with the Short robot’s request, demonstrating an opposite pattern to human dynamics. We conclude that while height has a substantial social impact on human-robot interactions, it follows a unique pattern of influence. Our findings suggest that designers cannot simply adopt and implement elements from human social dynamics to robots without testing them first.
Michael Faber, Andrey Grishko, Julian Waksberg, David Pardo, Tomer Leivy, Yuval Hazan, Emanuel Talmansky, Benny Megidish, Hadas Erel
RO-MAN5