Demo Data from EDBT 2026 / reviewers in the wild / expert
Valentina Corbetta
dblp:304/4141
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—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.
| Artificial intelligence
1 paper |
Motion planning and robot control · 33% Planning, search and constraint satisfaction · 33% Robot navigation and mapping · 33% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping
obstacle avoidance |
0.5 | 1 | 2021 | Optimized 3D path planner for steerable catheters with deductive reasoning · ICRA 2021 |
Robotics › Motion planning and robot control
path planning |
0.5 | 1 | 2021 | Optimized 3D path planner for steerable catheters with deductive reasoning · ICRA 2021 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning under uncertainty
risk-aware planning |
0.5 | 1 | 2021 | Optimized 3D path planner for steerable catheters with deductive reasoning · ICRA 2021 |
Methods — techniques the papers use, named apart from their topics
deductive reasoning · 1.03d visualization · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Optimized 3D path planner for steerable catheters with deductive reasoningabstractKeyhole neurosurgery is challenging, due to the complex anatomy of the brain and the inherent risk of damaging vital structures while reaching the surgical target. This paper presents a path planner for safe and effective neurosurgical interventions. The strengths of the proposed framework lay in the integration of multiple risk structures combined into a deductive method for fast and intuitive user interaction, and a modular architecture. The tool is intended to support neurosurgeons at quickly determining the most appropriate surgical trajectory through the brain matter with minimized risk; the user interface guides the user through the decision making process and helps save planning time of neurosurgical interventions. Risk structures and trajectories can be visualized in an intuitive way, thanks to a 3D brain surgery simulator developed with Unity. A qualitative evaluation with clinical experts shows the practical relevance, while a quantitative performance and functionality analysis proves the robustness and effectiveness of the system with respect to literature. Alice Segato, Valentina Corbetta, Jessica Zangari, Simona Perri, Francesco Calimeri, Elena De Momi |
ICRA | 2 |