Papers

2

Total Citations

10

H-Index

2

About

Bei Hua is a rising researcher in human-robot interaction, with a focus on making autonomous robots safer and more emotionally resonant in human environments. Her work addresses two critical challenges: improving robot navigation in crowded spaces and enabling humanoid robots to generate meaningful facial expressions. In her 2023 paper on robot navigation, Hua introduces a novel approach by training a "non-cooperator" model to identify vulnerabilities in robot path planning, thereby enhancing robustness against unpredictable pedestrians. This work, already garnering 5 citations, offers a fresh perspective on safety in dynamic social settings. Simultaneously, her research on automatic facial expression generation tackles the mechanical and aesthetic diversity of humanoid robots, proposing a preference-based system to produce consistent, emotionally engaging expressions. With both papers published in 2023 and accumulating early citations, Hua is establishing herself as a thoughtful contributor to socially intelligent robotics. Her work bridges technical robustness with human-centered design, promising safer and more expressive robots for future coexistence.

Research Focus

Key Achievements

2
H-Index
2
Papers
10
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Training a Non-Cooperator to Identify Vulnerabilities and Improve Robustness for Robot Navigation
5 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of Science and Technology of China

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago