Emily Doherty
Papers
1
Total Citations
6
H-Index
1
About
Emily Doherty is a rising researcher at the intersection of human-robot interaction and cognitive neuroscience, with a focus on enabling more fluid, adaptive collaboration between humans and autonomous systems. Her key research areas include multi-agent systems, brain-computer interfaces, and the development of neural metrics for real-time human state estimation. In her most cited work, "Towards Brain Metrics for Improving Multi-Agent Adaptive Human-Robot Collaboration: A Preliminary Study" (2022, 6 citations), Doherty tackles a fundamental challenge in robotics: robots’ inability to perceive and respond to the subtle behavioral and neural cues humans naturally exchange during teamwork. By proposing a framework that integrates brain signals into robot decision-making, she lays the groundwork for robots that can dynamically adapt their actions to human intent and cognitive load. Though early in her career, her work has already been recognized for its interdisciplinary ambition, bridging engineering, psychology, and neuroscience. Doherty’s contributions promise to make human-robot teams safer, more efficient, and more intuitive—a critical step toward seamless collaboration in manufacturing, healthcare, and beyond.
Research Focus
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Top Papers
- 1