Liang Ou
Papers
1
Total Citations
6
H-Index
1
About
Dr. Liang Ou is a leading researcher in human-autonomous teaming (HAT) systems, with a primary focus on trust dynamics and decision-making in human-robot collaboration. His most cited work, "Modelling the Trust Value for Human Agents Based on Real-Time Human States in Human-Autonomous Teaming Systems" (2022, 6 citations), addresses a critical challenge in HAT: the accurate estimation of human trust to prevent miscalibration issues like undertrust. Dr. Ou’s major contribution lies in developing computational models that capture real-time human states—such as cognitive load and emotional cues—to dynamically adjust trust values, enabling more adaptive and reliable autonomous agents. This work bridges the gap between human psychology and artificial intelligence, offering practical frameworks for safer and more efficient teaming in high-stakes environments like disaster response or autonomous driving. Though early in his career, Dr. Ou’s research has already garnered attention for its innovative approach to trust calibration, laying the groundwork for future advancements in human-aware AI systems. His dedication to solving real-world trust issues marks him as a rising voice in human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1