Demo Data from VLDB 2026 / reviewers in the wild / expert
Jakub Glowacki
dblp:319/4915
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
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 |
Robot manipulation · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation › task automation
laboratory automation |
0.6 | 1 | 2022 | ARChemist: Autonomous Robotic Chemistry System Architecture · ICRA 2022 |
Robotics › Robot manipulation
task automation |
0.6 | 1 | 2022 | ARChemist: Autonomous Robotic Chemistry System Architecture · ICRA 2022 |
Methods — techniques the papers use, named apart from their topics
system architecture design · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | ARChemist: Autonomous Robotic Chemistry System ArchitectureabstractAutomated laboratory experiments have the potential to propel new discoveries, while increasing reproducibility and improving scientists' safety when handling dangerous materials. However, many automated laboratory workflows have not fully leveraged the remarkable advancements in robotics and digital lab equipment. As a result, most robotic systems used in the labs are programmed specifically for a single experiment, often relying on proprietary architectures or using unconventional hardware. In this work, we tackle this problem by proposing a novel robotic system architecture specifically designed with and for chemists, which allows the scientist to easily reconfigure their setup for new experiments. Specifically, the system's strength is its ability to combine together heterogeneous robotic platforms with standard laboratory equipment to create different experimental setups. Finally, we show how the architecture can be used for specific laboratory experiments through case studies such as solubility screening and crystallisation. Hatem Fakhruldeen, Gabriella Pizzuto, Jakub Glowacki, Andrew I. Cooper |
ICRA | 3 |