Will Seidelman
Papers
1
Total Citations
2
H-Index
1
About
Will Seidelman is a researcher at the intersection of human-robot interaction and advanced manufacturing, with a particular focus on welding technology. His work explores how visual augmentation systems can support both human welders and those supervising automated welding robots, or “welbots.” In his notable 2016 study, “Does an Abstract Weld Pool Visualization Help Novice Welders Assess the Performance of a Weldbot?” Seidelman investigated whether abstract visualizations of weld pool parameters could improve novice operators’ ability to evaluate robot performance. This research addresses a critical challenge in modern manufacturing: enabling less experienced workers to effectively monitor and assess complex automated processes. While his most-cited paper has garnered 2 citations, Seidelman’s contribution lies in pioneering the empirical study of human factors in robotic welding supervision. His work bridges cognitive science and industrial engineering, offering insights into how interface design can democratize access to skilled trades. By examining the cognitive load and decision-making of novice welders, Seidelman helps pave the way for more intuitive human-robot collaboration systems in manufacturing environments.
Research Focus
Key Achievements
Top Papers
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