Demo Data from SIGIR 2026 / reviewers in the wild / expert
Arrigo Croce
dblp:258/4479
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
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 |
Human-robot interaction · 100% | |
| Artificial intelligence
1 paper |
Robot manipulation · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
animal-robot interaction |
0.4 | 1 | 2020 | Model-Based Feedback Control of Live Zebrafish Behavior via Interaction With a Robotic Replica · IEEE Trans. Robotics 2020 |
Robotics › Robot manipulation › robot design
bio-inspired robot design |
0.1 | 1 | 2020 | Model-Based Feedback Control of Live Zebrafish Behavior via Interaction With a Robotic Replica · IEEE Trans. Robotics 2020 |
Methods — techniques the papers use, named apart from their topics
feedback control · 0.9data-driven behavior modeling · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Model-Based Feedback Control of Live Zebrafish Behavior via Interaction With a Robotic ReplicaabstractThe possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over twenty-five years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our understanding of animal behavior along new directions. Despite significant progress, most of the research has focused on open-loop control systems, in which robots execute predetermined actions, independent of the animal behavior. We integrate mathematical modeling of social behavior toward the design of realistic feedback laws for robots to interact with a live animal. In particular, we leverage recent advancements in data-driven modeling of zebrafish behavior. Ultimately, we establish a novel robotic platform that allows real-time actuation of a biologically-inspired 3D-printed zebrafish replica to implement model-based control of animal behavior. We demonstrate our approach through a series of experiments, designed to elucidate the appraisal of the replica by live subjects with respect to conspecifics and to quantify the biological value of closed-loop control. Pietro De Lellis, Edoardo Cadolini, Arrigo Croce, Yanpeng Yang, Mario di Bernardo, Maurizio Porfiri |
IEEE Trans. Robotics | 3 |