Demo Data from EDBT 2026 / reviewers in the wild / expert
Laura Moradbakhti
dblp:361/3111
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2026
0000-0001-8886-6906ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 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 |
Collaborative and social computing · 44% Health and well-being technologies · 44% Design research and methods · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Health and well-being technologies › user wellbeing
workplace well-being |
1.0 | 1 | 2026 | Understanding Workplace Relatedness Support among Healthcare Professionals: A Four-Layer Model and Implications for Technology Design · CHI 2026 |
Design research and methods › design workshops
co-design workshop |
0.3 | 1 | 2026 | Understanding Workplace Relatedness Support among Healthcare Professionals: A Four-Layer Model and Implications for Technology Design · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
semi-structured interviews · 1.0co-design workshops · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Understanding Workplace Relatedness Support among Healthcare Professionals: A Four-Layer Model and Implications for Technology DesignabstractHealthcare professionals (HCPs) face increasing occupational stress and burnout. Supporting HCPs’ need for relatedness is fundamental to their psychological wellbeing and resilience. However, how technologies could support HCPs’ relatedness in the workplace remains less explored. This study incorporated semi-structured interviews (n = 15) and co-design workshops (n = 21) with HCPs working in the UK National Health Service (NHS), to explore their current practices and preferences for workplace relatedness support, and how technology could be utilized to benefit relatedness. Qualitative analysis yielded a four-layer model of HCPs’ relatedness need, which includes Informal Interactions, Camaraderie and Bond, Community and Organizational Care, and Shared Identity. Workshops generated eight design concepts (e.g., Playful Encounter, Collocated Action, and Memories and Stories) that operationalize the four relatedness need layers. We conclude by highlighting the theoretical relevance, practical design implications, and the necessity to strengthen relatedness support for HCPs in the era of digitalization and artificial intelligence. Zheyuan Zhang 0003, Dorian Peters, Laura Moradbakhti, Andrew Hall, Rafael A. Calvo |
CHI | 5 |
| 2023 | Differing Care Giver and Care Receiver Perceptions of Robot Agency in an In-Home Socially Assistive Robot for Exercise EngagementabstractWe present the results of an online, video-based experimental study investigating the impact of robot agency on perceptions of a socially assistive robot (SAR) shown supporting in-home care. We consider two key participant groups: care givers and care receivers. We did not find significant results regarding the impact of agency on overall participant perceptions of the SAR, but we did identify some differences in what these two participant groups might perceive as being best for themselves versus each other. Firstly, care givers perceived more potential benefit from the robot than care receivers did, challenging possible assumptions about who is set to gain most from deployment of these systems. Secondly, care receivers generally perceived the lower agency robot as being more beneficial for themselves, even as they ascribed the higher agency robot more potential to benefit care receivers. Katie Winkle, Laura Moradbakhti |
RO-MAN | 2 |