Demo Data from VLDB 2026 / reviewers in the wild / expert
Christopher J. Peters
dblp:364/5347
· DBLP profile ↗
1ranked-venue papers
0as 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 since 2021Systems, architecture and hardware · 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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% | |
| Artificial intelligence
1 paper |
Motion planning and robot control · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics › surgical robotics
robot-assisted surgery |
0.9 | 1 | 2025 | Automatic Robotic-Assisted Diffuse Reflectance Spectroscopy Scanning System · ICRA 2025 |
Medical and health informatics › medical imaging › medical image analysis
tissue characterization |
0.9 | 1 | 2025 | Automatic Robotic-Assisted Diffuse Reflectance Spectroscopy Scanning System · ICRA 2025 |
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing |
0.3 | 1 | 2025 | Automatic Robotic-Assisted Diffuse Reflectance Spectroscopy Scanning System · ICRA 2025 |
Methods — techniques the papers use, named apart from their topics
hybrid visual servoing · 1.7diffuse reflectance spectroscopy · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Automatic Robotic-Assisted Diffuse Reflectance Spectroscopy Scanning SystemabstractDiffuse Reflectance Spectroscopy (DRS) is a wellestablished optical technique for tissue composition assessment which has been clinically evaluated for tumour detection to ensure the complete removal of cancerous tissue. While pointwise assessment has many potential applications, incorporating automated large-area scanning would enable holistic tissue sampling with higher consistency. We propose a robotic system to facilitate autonomous DRS scanning with hybrid visual servoing control. A specially designed height compensation module enables precise contact condition control. The evaluation results show that the system can accurately execute the scanning command and acquire consistent DRS spectra with comparable results to the manual collection, which is the current gold standard protocol. Integrating the proposed system into surgery lays the groundwork for autonomous intra-operative DRS tissue assessment with high reliability and repeatability. This could reduce the need for manual scanning by the surgeon while ensuring complete tumor removal in clinical practice. Kaizhong Deng, Christopher J. Peters, George P. Mylonas, Daniel S. Elson |
ICRA | 2 |