EDBT 2026 Demo / reviewers in the wild / expert
Zhehui Yin
dblp:408/0797
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2026
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2 · 2 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.
| Computer networks
2 papers |
Wireless sensing and localization · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless sensing and localization
mmwave sensing |
1.0 | 1 | 2026 | MuPose: Breaking the Scalability Barrier of mmWave Multi-User Pose Estimation in the Wild · MobiSys 2026 |
Wireless sensing and localization › radar sensing
mmwave radar sensing |
0.9 | 1 | 2025 | mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation Tilting · IEEE Trans. Mob. Comput. 2025 |
Wireless sensing and localization › human activity recognition
fall detection |
0.3 | 1 | 2025 | mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation Tilting · IEEE Trans. Mob. Comput. 2025 |
Wireless sensing and localization
vital sign monitoring |
0.3 | 1 | 2025 | mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation Tilting · IEEE Trans. Mob. Comput. 2025 |
Methods — techniques the papers use, named apart from their topics
radar orientation adjustment · 0.9automated calibration · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | MuPose: Breaking the Scalability Barrier of mmWave Multi-User Pose Estimation in the Wild
Zhehui Yin, Hongliu Yang, Zhiyun Yao, Zizhou Fan, Daqing Zhang 0001 |
MobiSys | 2 |
| 2025 | mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation TiltingabstractIndoor mmWave-based sensing technologies have garnered substantial interest from both the industrial and academic. Yet, the intrinsic challenge posed by the limited Field-of-View (FOV) of mmWave radars significantly restricts their coverage. This limitation necessitates careful selection of installation positions and orientations to optimize performance, thereby severely curtailing the versatility and widespread adoption of these systems. Traditionally, expanding coverage involved increasing the number of radar units. This paper introduces a novel approach to enhance the FOV by incorporating mobility, achieved by affixing the radar onto a pan-tilt unit capable of rotating along both the horizontal and azimuthal. Nevertheless, the disparity between the pan-tilt and the radar presents significant challenges for accurately rotating the radar's orientation. To mitigate this, we propose an automated calibration algorithm for radar and pan-tilt, ensuring precise calibration. Additionally, we have devised a radar orientation adjustment algorithm intended to automatically align the radar's FOV with the positions of detected objects to facilitate various applications. Through three case studies, we have demonstrated that mmRotation can greatly expand the sensing range, enabling support for multiple applications on a single radar, such as vital signs monitoring and fall detection. Comprehensive experimental results underscore that our system surpasses the current state-of-the-art (SOTA). Zhehui Yin, Yaxiong Xie, Hewen Wei, Zhaoxin Chang 0001, Daqing Zhang 0001 |
IEEE Trans. Mob. Comput. | 3 |