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Dezijian Zhou

dblp:404/5581 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · unresolved

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

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 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
Design research and methods · 44% Immersive interaction · 44% Health and well-being technologies · 13%

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

TopicWeightPapersLastEvidence papers
Immersive interaction
mixed reality interaction
0.912025
Participatory Design Investigation for Spatial Interactions in Ageing Population · HRI 2025
Design research and methods
participatory design
0.912025
Participatory Design Investigation for Spatial Interactions in Ageing Population · HRI 2025
Health and well-being technologies › elderly care
aging in place
0.312025
Participatory Design Investigation for Spatial Interactions in Ageing Population · HRI 2025

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

participatory design · 0.9mixed reality · 0.9
YearPublicationVenuePosition
2025 Participatory Design Investigation for Spatial Interactions in Ageing Population
abstract
With the accelerating growth of the aging population and changes in family structures, the demand for supportive living environments and social interaction among older adults has grown significantly. However, traditional qualitative methods often fail to fully capture the nuanced needs of older adults due to communication barriers, memory limitations, and psychological stress. This study proposes an innovative research approach using an AI-driven age-inclusive digital agent in Mixed Reality (MR) to explore long-term interactions with older adults ageing in place. By creating intelligent digital agents designed after individuals, pets, or objects familiar to older adults, these agents aim to unobtrusively investigate how the residential environment influences daily routines among older people. Insights gained through natural interactions in MR can inform the design of residential spaces, better satisfying the needs of aging populations. This proposed approach aims to improve both home redevelopments and future residential designs for older adults.
Dezijian Zhou, Jialing Xie, Wenkai Bian, Yuanyuan Deng, Anastasia Globa
HRI1