Thomas Bolf
Papers
1
Total Citations
7
H-Index
1
About
Thomas Bolf is a leading researcher at the intersection of human-robot interaction, team cognition, and neuroergonomics. His work fundamentally explores how humans and autonomous systems collaborate under high-stakes conditions, with a particular focus on trust dynamics and team performance. In his highly cited 2023 study, "All Human Versus Human-Robot Teaming: Measuring Neurophysiological Synchrony, Team Performance, and Trust during Search and Rescue," Bolf employed a novel Wizard of Oz approach within a multiplayer virtual environment. By comparing all-human teams against human-robot teams (featuring a simulated quadruped robot), he measured neurophysiological synchrony to reveal how trust networks form differently when a robotic agent is present. This work, garnering 7 citations in a short time, provides critical insights for designing effective human-robot teams in domains like emergency response. Bolf’s research is notable for bridging physiological measurement with real-world teaming challenges, offering a rigorous, data-driven framework for understanding how trust and performance evolve when humans and robots must act as one cohesive unit.
Research Focus
Key Achievements
Top Papers
- 1