Mark A. Roebke

Papers

Total Citations

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About

Mark A. Roebke is a leading voice in the study of human-machine teaming, with a primary focus on the psychological and social dynamics that underpin effective collaboration between humans and autonomous systems. His research bridges cognitive engineering and organizational trust, exploring how reliance, transparency, and communication shape performance in high-stakes environments. Roebke’s most influential work, a 2019 qualitative study on trust in human-machine teams, has garnered 64 citations and is widely recognized for reframing trust not as a static attribute but as a dynamic, context-dependent process. This paper has become a foundational reference for researchers designing adaptive automation and decision-support systems. Beyond this, Roebke has contributed to frameworks for measuring trust calibration and has been instrumental in developing training protocols that enhance human-robot interaction in military and healthcare settings. His work is distinguished by its rigorous qualitative methodology, offering deep insights often missed in quantitative models. Roebke’s impact is evident in how his findings inform both academic theory and practical system design, making him a key figure in the evolving dialogue on how humans and machines can work together safely and effectively.