Demo Data from SIGIR 2026 / reviewers in the wild / expert
Alberto Rota
dblp:314/0781
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2024
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 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 |
Learning and educational technologies · 62% Haptics and multimodal interaction · 38% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Learning and educational technologies › medical training
surgical robotics training |
0.8 | 1 | 2024 | Implementation and Assessment of an Augmented Training Curriculum for Surgical Robotics · ICRA 2024 |
Haptics and multimodal interaction
haptic feedback |
0.2 | 1 | 2024 | Implementation and Assessment of an Augmented Training Curriculum for Surgical Robotics · ICRA 2024 |
Haptics and multimodal interaction › haptic feedback
haptic guidance |
0.2 | 1 | 2024 | Implementation and Assessment of an Augmented Training Curriculum for Surgical Robotics · ICRA 2024 |
Methods — techniques the papers use, named apart from their topics
physics engine simulation · 0.8haptic interface · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Implementation and Assessment of an Augmented Training Curriculum for Surgical RoboticsabstractThe integration of high-level assistance algorithms in surgical robotics training curricula may be beneficial in establishing a more comprehensive and robust skillset for aspiring surgeons, improving their clinical performance as a consequence. This work presents the development and validation of a haptic-enhanced Virtual Reality simulator for surgical robotics training, featuring 8 surgical tasks that the trainee can interact with thanks to the embedded physics engine. This virtual simulated environment is augmented by the introduction of high-level haptic interfaces for robotic assistance that aim at re-directing the motion of the trainee’s hands and wrists toward targets or away from obstacles, and providing a quantitative performance score after the execution of each training exercise.An experimental study shows that the introduction of enhanced robotic assistance into a surgical robotics training curriculum improves performance during the training process and, crucially, promotes the transfer of the acquired skills to an unassisted surgical scenario, like the clinical one. Alberto Rota, Elena De Momi |
ICRA | 1 |