Amanda Siebert-Evenstone

Papers

Total Citations

108

H-Index

About

Amanda Siebert-Evenstone is a leading researcher in human-robot collaboration, specializing in the integration of collaborative robots (cobots) into industrial workplaces. Her work bridges the gap between automation technology and human factors, focusing on how workers and companies can effectively adopt cobots for flexible manufacturing. Her most cited paper, "Collaborative or Simply Uncaged? Understanding Human-Cobot Interactions in Automation" (2020, 90 citations), critically examines the realities of human-cobot collaboration, revealing that despite their intended cooperative design, many deployments fall short of true collaboration. This foundational work has shaped discussions on workplace automation and human-robot teaming. She also developed "CoFrame: A System for Training Novice Cobot Programmers" (2022, 15 citations), a practical tool addressing the critical skills gap in cobot programming. Her research emphasizes safety as a cornerstone of expertise, as seen in "Safety First: Developing a Model of Expertise in Collaborative Robotics" (2021). Siebert-Evenstone’s contributions are vital for students and practitioners seeking to understand the socio-technical challenges of implementing cobots safely and effectively in real-world settings.