Dave Shane
Papers
1
Total Citations
7
H-Index
1
About
Dave Shane’s research lies at the intersection of human-robot interaction, cognitive ergonomics, and workload management, with a focus on designing more intuitive and efficient teleoperation systems. His most-cited work, “Investigation of Multiple Resource Theory Design Principles on Robot Teleoperation and Workload Management” (2021, 7 citations), makes a significant contribution by empirically testing how audio feedback—often overlooked in visually dominated robot interfaces—can reduce cognitive load and improve operator performance. Drawing on Wickens’ Multiple Resource Theory, Shane designed a dual-task scenario involving search and threat-defusal alongside a memory test, demonstrating that distributing information across sensory channels enhances multitasking efficiency. This work has practical implications for military, search-and-rescue, and industrial robotics, where operators face high-stakes, information-rich environments. Though early in his career, Shane’s targeted application of established cognitive theory to real-world robotic systems marks him as a thoughtful innovator. His findings offer a clear, evidence-based path for interface designers seeking to mitigate operator overload without sacrificing mission effectiveness. For students and researchers, Shane’s work exemplifies how theory-driven experimentation can directly inform the design of safer, more capable human-robot teams.
Research Focus
Key Achievements
Top Papers
- 1