Peter E. Keller

Papers

Total Citations

H-Index

About

Peter E. Keller is a leading researcher in the cognitive neuroscience of music and human interaction, whose work bridges the gap between joint action, temporal processing, and human-robot collaboration. His primary contributions lie in understanding how individuals coordinate their movements in time—whether playing a duet or working alongside a machine. Keller’s most-cited paper, “Temporal adaptation and anticipation mechanisms to overcome the Out Of The Loop problem in HRI” (2022), proposes a groundbreaking framework for endowing robots with the same predictive timing mechanisms that humans use to synchronize and adapt during joint action. By tackling the “Out Of The Loop” phenomenon, his work directly addresses a critical challenge in human-robot interaction: keeping human operators engaged and responsive when automation fails. While his citation count is still growing, this paper has already shaped discussions in robotics and cognitive science, positioning Keller as a key figure in translating principles of musical ensemble coordination into practical engineering solutions. His research not only deepens our understanding of temporal cognition but also offers a roadmap for creating more intuitive, collaborative artificial agents.