EDBT 2026 Demo / reviewers in the wild / expert
Saurabh Dingwani
dblp:404/5751
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous 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.
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 67% Human-AI interaction · 33% | |
| Artificial intelligence
1 paper |
Robot manipulation · 100% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-AI interaction › large language model interaction › language-based interaction
natural language interface |
0.9 | 1 | 2025 | RCareGen: An Interface for Scene and Task Generation in RCareWorld · HRI 2025 |
Human-robot interaction
robot programming |
0.9 | 1 | 2025 | RCareGen: An Interface for Scene and Task Generation in RCareWorld · HRI 2025 |
Methods — techniques the papers use, named apart from their topics
large language model · 1.7code generation · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | RCareGen: An Interface for Scene and Task Generation in RCareWorldabstractThis late-breaking report presents RCareGen, a graphical interface that integrates natural language commands with RCare World, a physics simulator for robotic caregiving scenarios. RCareGen has three core modules: (1) a front-end web interface, (2) an LLM-based code generator, and (3) the RCareWorld simulation backend. The front-end web interface enables novice users to input natural language, which is translated into Python code by an LLM-based code generator. This generated code interacts with RCareWorld APIs to run the simulation backend, facilitating scene setup, modifications, simple movements, and human-robot interaction tasks. Additionally, the system supports iterative feedback, allowing users to refine scenes and tasks interactively. By simplifying simulation setup and enhancing task diversity, RCareGen introduces a novel interface that democratizes robot simulation and programming across diverse domains. Shuaixing Chen, Ruolin Ye, Saurabh Dingwani, Pooyan Fazli, Hasti Seifi, Tapomayukh Bhattacharjee |
HRI | 3 |