Manuel Baeriswyl
Papers
1
Total Citations
16
H-Index
1
About
Manuel Baeriswyl is a leading researcher at the intersection of Human–AI–Robot Teaming (HART) and remote research methodologies. His work addresses the critical challenges of studying complex human-machine interactions outside traditional lab settings, particularly highlighted in his highly cited 2021 paper, “Remote research methods for Human–AI–Robot Teaming,” which has garnered 16 citations. This foundational study systematically explored methodological adaptations necessitated by the COVID-19 pandemic, identifying key issues such as participant engagement, data fidelity, and the replication of physical presence in virtual environments. Baeriswyl’s contributions provide a vital framework for conducting rigorous, ecologically valid HART research remotely, enabling continued progress in fields like autonomous systems and collaborative robotics. His insights into the nuances of remote experimentation—from technical hurdles to social dynamics—have shaped best practices for a new generation of researchers. By pioneering these adaptive methods, Baeriswyl ensures that the study of human-AI-robot collaboration remains robust and scalable, even when face-to-face interaction is not possible.
Research Focus
Key Achievements
Top Papers
- 1Remote research methods for Human–AI–Robot Teaming16 citations · 2021