Demo Data from SIGIR 2026 / reviewers in the wild / expert
Luming Xu
dblp:267/4613
· 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 · 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.
| Computer networks
1 paper |
Wireless sensing and localization · 100% | |
| Artificial intelligence
1 paper |
Robot navigation and mapping · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 77% Medical and health informatics · 23% | |
| Human-computer interaction and pervasive computing
1 paper |
Ubiquitous computing and smart environments · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping
localization |
1.0 | 1 | 2026 | Mobi2Still: People Detection and Tracking With Mobile Human-Equipped mmWave Radars · IEEE Trans. Mob. Comput. 2026 |
Wireless sensing and localization › tracking
human detection and tracking |
1.0 | 1 | 2026 | Mobi2Still: People Detection and Tracking With Mobile Human-Equipped mmWave Radars · IEEE Trans. Mob. Comput. 2026 |
Wireless sensing and localization
mmwave sensing |
1.0 | 1 | 2026 | Mobi2Still: People Detection and Tracking With Mobile Human-Equipped mmWave Radars · IEEE Trans. Mob. Comput. 2026 |
Bioinformatics and computational biology › biomarker discovery
disease biomarker discovery |
0.6 | 1 | 2022 | PltDB: a blood platelets-based gene expression database for disease investigation · Bioinform. 2022 |
Ubiquitous computing and smart environments
mobile sensing |
0.3 | 1 | 2026 | Mobi2Still: People Detection and Tracking With Mobile Human-Equipped mmWave Radars · IEEE Trans. Mob. Comput. 2026 |
Medical and health informatics › clinical diagnosis › molecular diagnostics
liquid biopsy |
0.2 | 1 | 2022 | PltDB: a blood platelets-based gene expression database for disease investigation · Bioinform. 2022 |
Methods — techniques the papers use, named apart from their topics
velocity-aware calibration · 3.0mmwave radar · 3.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Mobi2Still: People Detection and Tracking With Mobile Human-Equipped mmWave RadarsabstractDue to the ability to penetrate darkness, smoke, and fog, wireless sensing technologies offer unique advantages for real-world deployments. Recent studies have mounted wireless sensing devices on mobile systems (such as drones and wheeled robots). Despite their promising potential, these approaches are predominantly designed for non-human platforms that exhibit limited mobility, typically involving translational movement with minimal rotation. When deployed on human carriers, however, the frequent body rotations and complex motion patterns significantly degrade their performance, due to the unpredictable changes in target position. In this paper, we propose Mobi2Still, which utilizes mobile human-equipped millimeter wave (mmWave) radars for people detection and tracking. The core idea is to match recurring environment information across different times to estimate radar motion in reverse, and based on this, enable accurate people detection and tracking. Specifically, Mobi2Still extracts geometric structure of scene objects which is radar-motion-independent to match the recurring environmental objects, thereby adapting both rotation and translation of mmWave radars. Furthermore, to improve Mobi2Still's generalization, we design a velocity-aware calibration mechanism to guide it to focus on scene-independent motion features. Experiments demonstrate that Mobi2Still can accurately detect and track people with 98.10% F1-score and 98.32% MOTA, achieving at least 7.54% F1-score (and 11.20% MOTA) improvements compared with state-of-the-art approaches. Dongzhu Xu, Hongli Zeng, Luming Xu, Huadong Ma, Anfu Zhou |
IEEE Trans. Mob. Comput. | 5 |
| 2022 | PltDB: a blood platelets-based gene expression database for disease investigationabstractMOTIVATION: Molecular profiling of blood-based liquid biopsies is a promising disease detection method, which overcomes the limitations of invasive diagnostic strategies. Recently, gene expression profiling of platelets reportedly provides valuable resource for developing new biomarkers for the detection of diseases, including cancer. However, there is no database containing RNAs in platelets. RESULTS: In this study, we constructed PltDB (http://www.pltdb-hust.com), a blood platelets-based gene expression database featuring integration and visualization of RNA expression profiles based on RNA-seq and microarray data spanning both normal individuals and patients with different diseases. PltDB currently contains the expression landscape of mRNAs, lncRNAs, circRNAs and miRNAs in platelets from patients with different disease types and healthy controls. Moreover, PltDB provides users with the tools for visualizing results of comparison and correlation analysis and for downloading expression profiles and analysis results. A submission interface for the scientific community is also embraced for uploading novel RNA expression profiles derived from platelet samples. PltDB will offer a comprehensive review of the clinical use of platelets, overcome technical problems when analyzing data from diverse studies and serve as a powerful platform for developing new blood biomarkers. AVAILABILITY AND IMPLEMENTATION: PltDB is accessible at http://www.pltdb-hust.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Danyi Zou, Luming Xu, Shijun Lei, Xingbo Li, Xiaohuan Lu, Xiaoqiong Li, Lin Wang 0070, Zheng Wang 0052 |
Bioinform. | 3 |