Demo Data from EDBT 2026 / reviewers in the wild / expert
Eimaan Saqib
dblp:345/2238
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
0000-0001-8467-6670ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-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 |
Ubiquitous computing and smart environments · 100% | |
| Network and information security
1 paper |
Privacy and data protection · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Ubiquitous computing and smart environments › smart home
smart home privacy |
0.9 | 1 | 2025 | Bystander Privacy in Smart Homes: A Systematic Review of Concerns and Solutions · ACM Trans. Comput. Hum. Interact. 2025 |
Privacy and data protection › image privacy
bystander privacy |
0.3 | 1 | 2025 | Bystander Privacy in Smart Homes: A Systematic Review of Concerns and Solutions · ACM Trans. Comput. Hum. Interact. 2025 |
Methods — techniques the papers use, named apart from their topics
systematic review · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Bystander Privacy in Smart Homes: A Systematic Review of Concerns and SolutionsabstractSmart home devices, such as security cameras and voice assistants, have seen widespread adoption due to the utility and convenience they offer to users. The deployment of these devices in homes, however, raises privacy concerns for bystanders—people who may not necessarily have a say in the deployment and configuration of these devices, and yet are exposed to or affected by their data collection. Examples of bystanders include guests, short-term tenants, and domestic workers. Prior work has studied the privacy concerns of different bystander groups and proposed design solutions for addressing these concerns. In this article, we present a systematic review of previous studies, describing how smart home bystanders are defined and classified, and illuminating the range of concerns and solutions proposed in the existing academic literature. We also discuss limitations in prior work, barriers to the uptake of research-based solutions by industry, and identify avenues for future research. Eimaan Saqib, Shijing He, Junghyun Choy, Ruba Abu-Salma, Jose M. Such, Julia Bernd, Mobin Javed |
ACM Trans. Comput. Hum. Interact. | 1 |