Papers
2
Total Citations
24
H-Index
2
About
Xinxing Yang is a pioneering researcher in multi-human multi-robot teaming, with a focus on trust dynamics and autonomous systems. Their key research areas include trust inference and propagation in heterogeneous teams, multi-modal sensor fusion, and computer vision for unmanned vehicles. Yang’s most notable contribution is the development of the Trust Inference and Propagation (TIP) model, which addresses a critical gap in human-robot interaction by enabling trust modeling beyond simple dyadic human-autonomy pairs. This work, published in 2023, has already garnered 21 citations, reflecting its significance in advancing team-of-teams coordination. Additionally, Yang has explored the design of multi-modal sensor fusion systems for unmanned vehicles, integrating computer vision to enhance autonomous navigation and perception. This research, with 3 citations, demonstrates practical applications in robotics and IoT. Yang’s work is instrumental in shaping how trust is understood and managed in complex, multi-agent environments, offering foundational insights for future human-robot collaboration. Their contributions are particularly valuable for researchers and students interested in trust dynamics, multi-robot systems, and autonomous vehicle technology.
Research Focus
Key Achievements
Top Papers
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