Max Robotics — Global Service Robot Directory + US Certification

About

Grace Teo is a leading researcher at the intersection of human factors engineering and robotics, specializing in human-robot teaming, workload assessment, and adaptive automation. Her work focuses on enhancing the effectiveness of human-robot collaboration by developing closed-loop systems that use real-time physiological measures—such as heart rate and brain activity—to dynamically adjust robot behaviors, thereby optimizing human performance and reducing cognitive overload. Teo’s most cited paper, “Enhancing the effectiveness of human-robot teaming with a closed-loop system” (2017, 24 citations), demonstrates how integrating operator workload states into robot control can improve team efficiency. Her foundational study, “Comparison of Measures Used to Assess the Workload of Monitoring an Unmanned System” (2015, 12 citations), critically evaluates workload metrics for unmanned systems, providing essential guidance for future research. Teo also bridges theory and practice in “The Relevance of Theory to Human-Robot Teaming Research and Development” (2016, 8 citations), advocating for theory-driven design. With a total of over 57 citations across her key works, Teo’s contributions are vital for creating safer, more intuitive human-robot teams in domains like defense, healthcare, and autonomous systems.