Huao Li
Papers
9
Total Citations
164
H-Index
5
About
Huao Li is a robotics and human-robot interaction researcher whose work sits at the intersection of autonomous systems, human trust, and multi-agent coordination. His research has made notable contributions to understanding how humans supervise and interact with robotic swarms operating at varied levels of autonomy — a challenging domain where cognitive complexity and uncertainty demand sophisticated human-machine frameworks. Li's most influential work, "Models of Trust in Human Control of Swarms With Varied Levels of Autonomy" (2019, 73 citations), established foundational computational models for quantifying human trust across manual, mixed-initiative, and fully autonomous control paradigms. This line of inquiry extends into Kalman estimation approaches and deep learning transparency, reflecting a commitment to making autonomous systems more interpretable and trustworthy. His research on leader-follower navigation and leader identity concealment addresses critical resilience challenges in swarm robotics, exploring how multi-agent reinforcement learning can protect mission-critical information. Beyond technical systems, Li has examined the cultural dimensions of robot normativity, investigating how diverse human populations perceive domestic robot behavior — broadening the field's understanding of socially embedded robotics. With cumulative citations exceeding 160, his work meaningfully advances both the theoretical and applied frontiers of human-swarm interaction and autonomous system design.
Research Focus
Key Achievements
Top Papers
- 1Models of Trust in Human Control of Swarms With Varied Levels of Autonomy73 citations · 2019
- 2Deep learning, transparency, and trust in human robot teamwork29 citations · 2020
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- 4Perceptions of Domestic Robots' Normative Behavior Across Cultures21 citations · 2019
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- 7Human Interaction Through an Optimal Sequencer to Control Robotic Swarms3 citations · 2018
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